U.S. patent application number 11/020969 was filed with the patent office on 2006-06-22 for position error signal quality.
This patent application is currently assigned to Seagate Technology LLC. Invention is credited to Timothy Francis Ellis, Mehmet Fatih Erden, Richard L. Keizer, Alexei H. Sacks.
Application Number | 20060132949 11/020969 |
Document ID | / |
Family ID | 36586451 |
Filed Date | 2006-06-22 |
United States Patent
Application |
20060132949 |
Kind Code |
A1 |
Erden; Mehmet Fatih ; et
al. |
June 22, 2006 |
POSITION ERROR SIGNAL QUALITY
Abstract
In a method for generating a confidence level of a position
error signal (PES) component that is indicative of a quality of the
PES component, a PES component is generated using position signal
samples of a read back signal corresponding to a servo burst
pattern. Next, a noise level corresponding to noise in the read
back signal is extracted using the position signal samples. A
confidence level is then generated based on the PES component and
the noise level. A system for performing the method includes a
transformation block, a position error signal (PES) component
extractor, a noise extractor, and a confidence level generator. The
transformation block is configured to receive position signal
samples of a read back signal corresponding to a servo burst
pattern taken at a sampling frequency. A transformed domain
representation of the position signal samples is then generated by
the transformation block based on the sampling frequency and the
servo burst pattern. The PES component extractor is configured to
extract a PES component of a PES based on the position signal
samples. The noise extractor is configured to extract a noise level
from the transformed domain representation. The confidence level
generator is configured to generate a confidence level that is
indicative of a quality of the PES component based on the PES
component and the noise level.
Inventors: |
Erden; Mehmet Fatih;
(Pittsburgh, PA) ; Keizer; Richard L.;
(Minnetonka, MN) ; Sacks; Alexei H.; (Edina,
MN) ; Ellis; Timothy Francis; (Tonka Bay,
MN) |
Correspondence
Address: |
SEAGATE TECHNOLOGY LLC C/O WESTMAN;CHAMPLIN & KELLY, P.A.
SUITE 1400 - INTERNATIONAL CENTRE
900 SECOND AVENUE SOUTH
MINNEAPOLIS
MN
55402-3319
US
|
Assignee: |
Seagate Technology LLC
Scotts Valley
CA
|
Family ID: |
36586451 |
Appl. No.: |
11/020969 |
Filed: |
December 22, 2004 |
Current U.S.
Class: |
360/31 ;
G9B/5.216 |
Current CPC
Class: |
G11B 5/596 20130101 |
Class at
Publication: |
360/031 |
International
Class: |
G11B 27/36 20060101
G11B027/36 |
Claims
1. A method of generating a confidence level of a position error
signal (PES) component produced by a servo control system, the
method comprising: a) generating a PES component using position
signal samples of a read back signal corresponding to a servo burst
pattern; b) extracting a noise level corresponding to noise in the
read back signal using the position signal samples; and c)
generating a confidence level based on the PES component and the
noise level, wherein the confidence level is indicative of a
quality of the PES component.
2. The method of claim 1, wherein the extracting step b) includes:
generating a transform domain representation of the position signal
samples based on the sampling frequency and the burst pattern; and
extracting the noise level from the transform domain
representation.
3. The method of claim 2, wherein the generating a transform domain
representation of the position signal samples includes multiplying
the position signal samples with a transformation matrix to form
the transformed domain representation in the form of a vector that
includes noise components relating to noise in the read back signal
and a position signal component corresponding to the PES
component.
4. The method of claim 3, wherein the extracting step b) includes:
identifying the noise component having a maximum absolute value;
and setting the noise level to the noise component having the
maximum absolute value.
5. The method of claim 3, wherein the extracting step b) includes
setting the noise level to an absolute value of the noise component
of the transformed domain representation that is likely to
correspond to a dominant noise component of the read back
signal.
6. The method of claim 1, wherein: the generating step c) includes
calculating a ratio of the PES component to the noise level; and
the method includes comparing the ratio to a threshold value.
7. The method of claim 6 including setting the confidence level to
the ratio when the ratio is less than the threshold value.
8. The method of claim 6 including setting the confidence level to
a predefined constant value when the ratio is greater than the
threshold value.
9. A method of generating confidence level of a position error
signal (PES) component produced by a servo control system that is
indicative of a quality of the PES component, the method
comprising: a) obtaining position signal samples of a read back
signal corresponding to a servo burst pattern taken at a sampling
frequency; b) generating a transform domain representation of the
position signal samples based on the sampling frequency and the
burst pattern; c) generating a PES component based on a position
signal component of the transformed domain representation; d)
extracting a noise level from the transformed domain representation
corresponding to noise in the read back signal; and e) generating a
confidence level based on the PES component and the noise
level.
10. The method of claim 9, wherein the generating step b) includes
multiplying the position signal samples with a transformation
matrix to form the transformed domain representation in the form of
a vector that includes noise components relating to noise in the
read back signal and a position signal component corresponding to
the PES components.
11. The method of claim 10, wherein the extracting step d)
includes: identifying the noise component having a maximum absolute
value; and setting the noise level to the noise component having
the maximum absolute value.
12. The method of claim 10, wherein the extracting step d) includes
setting the noise level to an absolute value of the noise component
of the transformed domain representation that is likely to
correspond to a dominant noise component of the read back
signal.
13. The method of claim 9, wherein the generating step e) includes
comparing the PES component and the noise level.
14. The method of claim 13, wherein: the comparing of the PES
component and the noise level includes calculating a ratio of the
PES component to the noise level; and the method includes comparing
the ratio to a threshold value.
15. The method of claim 14 including: setting the confidence level
to the ratio when the ratio is less than the threshold value; and
setting the confidence level to a predefined constant when the
ratio is greater than the threshold value.
16. A servo control system configured to control a position of a
transducing head in response to position signal samples of a read
back signal corresponding to a servo burst pattern taken at a
sampling frequency, the system comprising: a transformation block
having a transformed domain representation output of the position
signal samples; a position error signal (PES) component extractor
having a PES component output corresponding to the servo burst
pattern, which is based on the position signal samples; a noise
extractor having a noise level output corresponding to noise in the
read back signal, which is based on the transformed domain
representation; and a confidence level generator having a
confidence level output that is indicative of a quality of the PES
component based on the PES component output and the noise level
output.
17. The system of claim 16, wherein the transformation block
includes a plurality of multipliers, each having an output based on
a multiplication of the position signal samples with a row of a
transformation matrix, and summing blocks each having an output of
a vector component of the transformed domain representation.
18. The system of claim 17, wherein: the vector components of the
transformed domain representation include noise components relating
to noise in the read back signal and a position signal component
corresponding to the PES component; and the noise extractor
includes a comparator having the noise level output corresponding
to a maximum of a plurality of noise component inputs.
19. The system of claim 18, wherein the confidence level generator
includes: an inverter including an inverted noise level output
corresponding to an inversion of the noise level output; and a
multiplier having a confidence level ratio output corresponding to
a multiplication of the inverted noise level output with the PES
component output; wherein the confidence level generator is
configured to produce the confidence level based on the confidence
level ratio output.
20. The system of claim 19 including a comparator including the
confidence level output and inputs of the confidence level ratio
output and a threshold value, wherein the confidence level output
is set to a predetermined constant when the confidence level ratio
output exceeds the threshold value, and the confidence level output
is set to the confidence level ratio output when the confidence
level ratio output is less than the threshold value.
Description
FIELD OF THE INVENTION
[0001] The present invention relates generally to servo control
systems of data storage devices, and more particularly but not by
limitation to circuitry and methods for establishing a confidence
level that is indicative of a quality of a position error signal
component used in servo control systems to establish a position of
a head.
BACKGROUND OF THE INVENTION
[0002] A typical disc drive comprises a plurality of rigid magnetic
storage discs which are axially aligned and arranged about a
spindle motor for rotation at a constant high speed (such as around
10,000 revolutions per minute). An array of read/write heads are
provided to transfer data between tracks of the discs and a host
computer in which the disc drive is mounted. The heads are mounted
to a rotary actuator assembly and are controllably positioned
adjacent the tracks by a closed loop servo control system.
[0003] The servo control system primarily operates in one of two
selectable modes: seeking and track following. A seek operation
entails moving a selected head from an initial track to a
destination track on the associated disc surface through the
initial acceleration and subsequent deceleration of the head away
from the initial track and toward the destination track. A velocity
control approach is used whereby the velocity of the head is
repeatedly measured and compared to a velocity profile defining a
desired velocity trajectory for the seek. Once the head has settled
on the destination track, the servo system enters a track following
mode of operation wherein the head is caused to follow the
destination track until the next seek operation is performed.
[0004] Both track seeking and track following operations typically
require generation of a position error signal (PES) which gives an
indication of the radial position of the head with respect to the
tracks on the disc. In high performance disc drives, the PES is
derived from either a prerecorded servo disc with a corresponding
servo head (a dedicated servo system), or from servo information
that is embedded on each recording surface among user data blocks
at predetermined intervals (an embedded servo system).
[0005] The head provides the servo information to the servo system
which generates the PES with a magnitude that is typically equal to
zero when the head is positioned over the center of the track ("on
track"), and is nominally linearly proportional to a relative
off-track distance between the head and the center of the
track.
[0006] The track center for reading and writing is generally
defined by servo bursts patterns or fields that are read by the
read head as a read back signal. The burst patterns typically
comprise a Null Pattern that causes amplitude components of the PES
to approach zero amplitude when the head is positioned between two
tracks. At such low levels, noise in the system can dominate the
PES components thereby reducing the quality of the PES components.
As a result, position information that is obtained using such low
quality PES components may be unreliable.
[0007] Embodiments of the present invention provide solutions to
these and other problems, and offer other advantages over the prior
art.
SUMMARY OF THE INVENTION
[0008] The present invention is generally directed to methods and
servo control systems for generating a confidence level of a
position error signal (PES) component that is indicative of a
quality of the PES component. In the method, a PES component is
generated using position signal samples of a read back signal
corresponding to a servo burst pattern. Next, a noise level
corresponding to noise in the read back signal is extracted using
the position signal samples. A confidence level is then generated
based on the PES component and the noise level.
[0009] In accordance with one embodiment of the method, the step of
extracting a noise level is performed by generating a transformed
domain representation of the position signal samples in the form of
a vector that includes noise components relating to noise in the
read back signal and a position signal component corresponding to
the PES component. In accordance with additional embodiments of the
method, the noise component having a maximum absolute value
relative to the other noise components is set as the noise level.
In accordance with one embodiment of the invention, the confidence
level is generated by first calculating a confidence level ratio of
the PES component to the noise level. The confidence level is then
set based on a comparison between the ratio and a threshold
value.
[0010] The servo control system of the present invention includes a
transformation block, a position error signal (PES) component
extractor, a noise extractor, and a confidence level generator. The
transformation block is configured to receive position signal
samples of a read back signal corresponding to a servo burst
pattern taken at a sampling frequency. A transformed domain
representation of the position signal samples is then generated by
the transformation block based on the sampling frequency and the
servo burst pattern. The PES component extractor is configured to
extract a PES component of a PES based on the position signal
samples. The noise extractor is configured to extract a noise level
from the transformed domain representation. The confidence level
generator is configured to generate a confidence level that is
indicative of a quality of the PES component based on the PES
component and the noise level.
[0011] In accordance with one embodiment of the system, the
transformation block includes a plurality of multipliers, each
configured to output a multiplication of the position signal
samples with a row of a transformation matrix, and summing blocks
configured to receive the outputs from the multipliers and produce
vector components of the transformed domain representation. The
vector components of the transformed domain representation include
noise components corresponding to noise in the read back signal and
a position signal component corresponding to the PES component. One
embodiment of the extractor block includes a comparator configured
to receive absolute values of the noise components and output a
maximum thereof as the noise level. One embodiment of the
confidence level generator includes an inverter configured to
invert the noise level, and a multiplier configured to multiply the
inverted noise level with an absolute value of the PES component to
thereby produce a confidence level ratio. The confidence level
generator is configured to produce the confidence level based on
the confidence level ratio.
[0012] Other features and benefits that characterize embodiments of
the present invention will be apparent upon reading the following
detailed description and review of the associated drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0013] FIG. 1 is an isometric view of a disc drive.
[0014] FIG. 2 illustrates a servo system for controlling a head
slider position in a disc drive.
[0015] FIG. 3 illustrates servo sector formatting on a disc of a
disc drive.
[0016] FIG. 4 is a block diagram of a servo demodulator of the
servo system shown in FIG. 2.
[0017] FIG. 5 is a block diagram of a data path for a PES component
extractor of a servo demodulator.
[0018] FIG. 6 is a flowchart illustrating a method of generating a
confidence level of a PES component, in accordance with embodiments
of the invention.
[0019] FIGS. 7-9 are block diagrams of portions of a servo control
system in accordance with embodiments of the invention.
[0020] FIG. 10 is a plot of amplitude versus normalized frequency
of sampled noisy read back signals corresponding to a servo burst
pattern or field for different off-track values.
[0021] FIG. 11 is a plot of amplitude versus normalized frequency
of the correlator signal of FIGS. 5 and 9.
[0022] FIG. 12 is a plot of amplitude versus normalized frequency
of a noise correlator h, together with a signal correlator hd of
FIG. 9.
[0023] FIGS. 13A-13D are plots of confidence levels for 100 sectors
corresponding to the PES component of the PS1 field when the servo
system architecture of FIG. 9 is used.
[0024] FIGS. 14A-14D are plots of the confidence levels for 100
sectors corresponding to the PES component of the PS1 field when
the servo system architecture of FIG. 8 is used.
DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS
[0025] FIG. 1 is an isometric view of a disc drive 100 in which
embodiments of the present invention are useful. The disc drive 100
includes a housing with a base 102 and a top cover (not shown). The
disc drive 100 further includes a disc pack 106, which is mounted
on a spindle motor (not shown) by a disc clamp 108. The disc pack
106 includes a plurality of individual discs, which are mounted for
co-rotation about a central axis 109, as indicated by arrow 107.
Each disc surface has an associated disc head slider 110 which is
mounted to the disc drive 100 for communication with the disc
surface. In the example shown in FIG. 1, sliders 110 are supported
by suspensions 112 which are in turn attached to track accessing
arms 114 of an actuator 116. The actuator shown in FIG. 1 is of the
type known as a rotary moving coil actuator and includes a voice
coil motor (VCM), shown generally at 118. The voice coil motor 118
rotates the actuator 116 with its attached heads 110 about a pivot
shaft 120 to position the heads 110 over a desired data track along
an arcuate path 122 between a disc inner diameter 124 and a disc
outer diameter 126. The voice coil motor 118 is driven by servo
electronics 130 based on signals generated by the heads 110 and a
host computer (not shown).
[0026] FIG. 2 illustrates a servo system 150 for controlling a
position 160 of a transducing head slider (such as head slider 110
in FIG. 1) relative to a track on a disc. The servo system 150 is
arranged as a control loop that includes a controller 152, a plant
156, a servo demodulator 166, and a summing junction 164.
[0027] The summing junction 164 receives a reference position
output signal 170 (r) and a position estimate output signal 168
({circumflex over (.tau.)}). The reference position output signal
170 indicates a desired head position relative to a center of a
track that is being read. The summing junction 164 calculates the
difference between the desired and estimated signals 170 and 168 to
provide the error output 158 that is representative of a desired
adjustment of the position of the head slider.
[0028] The error output 158 is provided to the controller 152,
which in turn produces a control output 154 for the plant 156. The
plant 156 is configured to move the position of the transducing
head toward the desired position indicated by signal 170, based on
the control output 154. The control output 154 typically comprises
a voice coil current, or an output to a microactuator, that is
provided to a voice coil motor (such as VCM 118) or a microactuator
of the plant 156, which responsively moves the head slider toward
the desired position.
[0029] The plant 156 represents the magnetic (or possibly optical)
recording system whose servo data output signal 162 is a read back
signal with servo specific position information. The read back
signal is produced in response to sensing of servo sectors on the
recording medium, such as a disc (such as disc of disc pack 106 in
FIG. 1), by a transducing read head of the head slider. The servo
sectors include pre-recorded position data for each track including
servo burst patterns that are used to generate a position error
signal (PES) in the read back signal 162 that indicates a position
of the head relative to a center of the current track. Accordingly,
the read back signal 162 corresponding to the servo data can be
used to obtain current position information for the head slider
including a current track and a location of the head relative to a
center of the current track.
[0030] The read back signal 162 is provided to the servo
demodulator 166, which includes circuitry that demodulates and
decodes the position data to extract the PES and the current track
position, which is provided in the position estimate output signal
168. When the desired position of the head indicated by the
reference signal 170 is set to zero for track center, the
difference between the position estimate signal 168 and the
reference or desired position signal 170 will be the PES once the
head is positioned over the desired track. However, the desired
position of the head may be an offset value from the center of the
track. As a result, once the head is positioned over the desired
track, the error output 158 may consist of a difference between a
desired PES representative of a desired position within the track
and the actual or estimated PES produced by the servo demodulator
that is representative of the current position of the head relative
to a center of the track.
[0031] A more detailed discussion of the operation of the servo
demodulator 166 will be provided with reference to FIGS. 3 and 4.
FIG. 3 illustrates an enlarged portion of an example of a typical
servo sector (also called embedded servo) format 200 on a disc in a
disc drive. As explained above, the read back signal 162
corresponding to each servo sector field is processed by the servo
demodulator, a exemplary architecture of a servo demodulator 300 in
accordance with embodiments of the invention is provided in FIG.
4.
[0032] It is understood by those skilled in the art that the
portion of the servo sector 200 illustrated in FIG. 3 is greatly
enlarged so that the track portions appear to be in straight lines,
but are actually part of circular tracks on a disc. During disc
drive operation, a read/write head moves relative to the disc from
left to right along an arc, such as arc 202, and produces a read
back signal (such as read back signal 162 in FIG. 2). The read back
signal includes data from servo sector fields of the servo sector.
The read back signal is then processed by a servo demodulator (such
as servo demodulator 166 in FIG. 2).
[0033] Referring now to FIG. 3, as the read head moves along the
track 202, it first reads data sector 204 and then the space PAD1
206 and then begins reading the servo sector starting with a
PLL/AGC field 208. The data written in the field 208 is the same
all along the cross-track direction. Using the data received from
the PLL/AGC field 208, an automatic gain controller (AGC) 302 (FIG.
4) provides an AGC output 304 that adjusts a gain of a variable
gain amplifier (VGA) 306. The variable gain amplifier 306 amplifies
the read back signal 310. The variable gain amplifier 306 provides
an amplified output 311 that couples through a cascade of circuits
including continuous time filter (CTF) 312, a sampling switch 314,
an analog-to-digital (A/D) converter 316, a digital finite impulse
response (DFIR) circuit 318 and a threshold detector 320. An
equalizer 319 in the DFIR 318 provides updated outputs every T, but
filtering in the DFIR 318 waits for 4T and gets 4 samples to output
every other 4T, and the threshold detector 320 operates on signals
every other 4T. The equalizer 319 is referred to as a "4T
equalizer" since it is optimized for a subsequent filter which
waits for 4 samples before providing output. A timing recovery (TR)
circuit 308 senses an output 322 from the A/D converter 316 or,
alternatively, an output 324 from the DFIR 318, to recover the
phase and frequency offset from the read back signal to control
sampling at the sampling switch 314 at the correct sampling
instances.
[0034] Next, a SAM/SIM field 210 (FIG. 3) is read. The SAM/SIM
field 210 stores the same data for Servo Address Mark (SAM) or
Servo Index Mark (SIM) for all the cross-track direction. The
variable gain amplifier 306 and the timing recovery circuit 308 are
adjusted prior to reading the SAM/SIM field, and the servo
demodulator circuit 300 (FIG. 4) is ready to demodulate the read
back data from the SAM/SAM field 210. Once the SAM/SIM information
is detected using the SAM/GRAY circuit 326, the SAM/GRAY circuit
326 then detects the gray-coded Track ID 212 (FIG. 3). Once the
Track ID 212 of the next desired track is correctly detected, the
magnetic head is presumed to be in the vicinity of the center line
of the desired track. After an additional space PAD 2 at 214, the
head reads Position Signal 1 (PS1) field or servo burst pattern 216
and Position Signal 2 (PS2) field or servo burst pattern 218, which
are separated by another space PAD3 at 220.
[0035] The servo demodulator circuit 300 (FIG. 4) processes the
data in PS1 and PS2 using a PES Extract circuit 328 to extract and
provide a position estimate output 330 (corresponding to position
estimate output 168 in FIG. 2). As mentioned above, the position
estimate output 168 and the position error signal 158 or 330 (FIG.
4) are often the same value because the reference position output
(desired PES) is usually zero for the center of the track. With the
use of the error signal 158, the servo system 150 (FIG. 1B) moves
the read/write head toward the desired position.
[0036] After the PS2 field 218, a Write Splice space 222 is
provided, followed by a Repeatable Run Out (RRO) Address Mark (AM)
224. The address mark 224 is detected with the help of "SAM/GRAY"
circuit 326 (FIG. 4), and a W-RRO field 226 associated with the
write process (W-RRO) is detected. A read R-RRO field 228 is also
detected. An RRO circuit 332 processes R-RRO and W-RRO information
to be used during the read or write processes, respectively, to
make the final adjustments on the head location against the RRO
effects in the system before the head starts writing or reading
data sectors.
[0037] Because of the limitations of the servo loop latency in FIG.
2, the servo demodulator block 166 has to complete all the
above-described functionalities within few clock cycles. Thus, each
sub block in FIG. 4 should be simple to implement, yet effective to
locate the magnetic head at the center of track during writing or
reading data tracks. This is also true for extracting the PES
signal components with the PES component extractor 328 using the
PS1 and PS2 fields.
[0038] FIG. 5 is a block diagram of the data path for the PES
component extractor 328 of the servo demodulator 300. The PES
component extractor 328 processes the PS1 and PS2 fields (FIG. 3)
of the read back signal 310 by first correlating the output 322 of
the A/D converter 316 with a suitable correlator, such as
correlator 340, with a correlating signal 342, such as d(k+.phi.),
that determines the sampling of the position signal samples 322 in
accordance with the servo burst patterns or fields SP1 and SP2 and
other factors. The PES component extractor 328 also includes a
summing block 350, at which the extracted samples 352 are summed to
thereby generate the PES component 330.
[0039] The parameter .phi. stands for the modulator phase error,
which will be assumed to be for a Null Pattern for the PS1 and PS2
fields to simplify the discussion of the PES component extractor
328. After processing the PS1 field by summing the corresponding
samples 352 of the read back signal 310, the PES component
extractor 328 outputs a number PES.sub.n(.epsilon.), which is the
normal or in-phase component of the PES 330, where .epsilon.
represents the amount of off-track. After processing the PS2 field,
the PES component extractor 328 outputs another number
PES.sub.q(.epsilon.), which is the quadrature component of the PES
330.
[0040] The normal and quadrature components of the PES 330 can be
further processed to obtain their Seamless representations. The
normal (S.sub.n) and quadrature (S.sub.q) components of the
Seamless representation are determined in accordance with Equations
1 and 2 below. The Seamless pair is provided to a final
linearization block to obtain the error signal 158 (FIG. 2) for the
controller 152 in the servo system 150. S n .function. ( ) = PES n
.function. ( ) PES n .function. ( ) + PES q .function. ( ) Eq .
.times. 1 ##EQU1## S q .function. ( ) = PES q .function. ( ) PES n
.function. ( ) + PES q .function. ( ) Eq . .times. 2 ##EQU2##
Confidence Level Generation
[0041] In the conventional method explained above, the PES
component extractor 328 outputs 2 numbers PES.sub.n(.epsilon.) and
PES.sub.q(.epsilon.) as a function of off-track amount (.epsilon.)
for each PS1 and PS2 fields. However, if the magnetic head is, for
example, in the middle of either of the two servo burst patterns
PS1 or PS2, the magnetization from upper portion of the pattern
will cancel the magnetization of the lower portion of the pattern.
Hence we will have no amplitude component to the signal from which
to estimate the PES. As a result, the SNR at that time will be zero
and the PES amplitude component will generally correspond to the
amplitude of noise (i.e., noise level) in the read back signal and
will not be an accurate representation of the desired position
error. The present invention provides additional information about
the quality of the PES components in the form of a confidence
level, which can be further utilized to improve the performance of
the system.
[0042] FIG. 6 is a flowchart illustrating a method of generating a
confidence level C of a position error signal (PES) component
produced by a servo control system that is indicative of a quality
of the PES component. At step 360 of the method, a PES component is
generated using position signal samples 352 (FIG. 5) of the read
back signal 310 corresponding to a servo burst pattern or field.
Thus, the position signal samples 352 can correspond to one of the
servo burst patterns or fields PS1 or PS2 and be used to generate
the normal and quadrature PES components.
[0043] At step 362, a noise level N corresponding to noise in the
read back signal 310 is extracted from the position signal samples
352. Preferably, the noise level is the dominant (i.e., maximum
amplitude) noise level or component in the read back signal.
Finally, at step 364, the confidence level C is generated based on
the noise level and the PES component.
[0044] FIG. 7 is a block diagram of a portion of a servo control
system that is configured to implement the method of FIG. 6. The
system of FIG. 7 includes the VGA 306, the CTF 312, and the A/D
converter 316, which are described above with respect to FIG. 5.
Additionally, the servo control system includes a transformation
block 370, a PES component extractor 372, a noise extractor 374,
and a confidence level generator 376.
[0045] The transformation block 370 is configured to receive the
(correlated) position signal samples from the AID converter 316 and
generate a transformed domain representation output (transformed
vector {overscore (y)}) of the position signal samples based on the
sampling frequency and the servo burst pattern corresponding to the
noisy read back signal 310. This conversion is generally
accomplished using a transform, which is based on the read back
signal sampling frequency and the servo burst pattern or field
corresponding to the read back signal samples 352.
[0046] An explanation of the conversion of the position signal
samples 352 to their transform domain representation will be
provided based on the exemplary servo burst patterns or fields PS1
and PS2 provided in FIG. 3, which are in the form of Null Patterns.
Those skilled in the art understand that other servo burst patterns
or fields can be used, which will have corresponding transforms
that may differ from that used with the exemplary burst patterns
shown in FIG. 3.
[0047] For the Null Patterns of PS1 and PS2, the Hadamard transform
is used to generate the desired transform domain representation of
the position signal samples. The Hadamard transform is a linear
transform which is represented by its associated transformation
matrix H. In general, the Hadamard domain representation {overscore
(y)} of a vector {overscore (x)} (e.g., the position signal samples
352) is obtained by multiplying the vector {overscore (x)} with the
transformation matrix H, as shown in Equation 3. y _ = H ^ .times.
x _ Eq . .times. 3 ##EQU3## Some basic properties of the Hadamard
transformation matrix H include the following: the elements of H
are +1's or -1's; H is a square matrix; and H is orthogonal (i.e. H
^ .times. H ^ N N T = N .times. I ^ N , ##EQU4## where N is the
size of H, H.sup.T represents the transpose of H, and I.sub.N
stands for the identity matrix with size N).
[0048] There are different methods that can be used to construct
the Hadamard matrix. However, the most common method is provided in
Equation 4, where H.sub.2 is defined in accordance with Equation 5.
As can be seen, this specific construction method of the Hadamard
matrix requires N to be an integer power of 2. Although, other
methods can be used to construct the Hadamard matrices when N is
not necessarily a power of 2, the construction mechanism described
above will be used to simplify the discussion of the present
invention. H ^ N = [ H ^ N / 2 H ^ N / 2 H ^ N / 2 - H ^ N / 2 ] Eq
. .times. 4 H ^ 2 = [ 1 1 1 - 1 ] Eq . .times. 5 ##EQU5##
[0049] A closer look at the construction of a few Hadamard matrices
will now be provided. Using the Hadamard matrix H.sub.2 provided in
Equation 5 together with Equation 4, H.sub.4 can be found as
provided in Equation 6: H ^ 4 = [ 1 1 1 1 1 - 1 1 - 1 1 1 - 1 - 1 1
- 1 - 1 1 ] Eq . .times. 6 ##EQU6## Then, using Equation 6 with
Equation 4, H.sub.8 can be obtained as provided in Equation 7. H ^
8 = [ 1 1 1 1 1 1 1 1 1 - 1 1 - 1 1 - 1 1 - 1 1 1 - 1 - 1 1 1 - 1 -
1 1 - 1 - 1 1 1 - 1 - 1 1 1 1 1 1 - 1 - 1 - 1 - 1 1 - 1 1 - 1 - 1 1
- 1 1 1 1 - 1 - 1 - 1 - 1 1 1 1 - 1 - 1 1 - 1 1 1 - 1 ] Eq .
.times. 7 ##EQU7## If we want to get H.sub.16, then we use H.sub.8
above together with Equation 4, and so on. Because of their
specific construction method, the complexity of these matrices are
on the order of N log N, like the fast Fourier transform.
[0050] The Hadamard matrices have several useful properties. For
instance, because of the orthogonality property, the rows (or
columns) of those matrices can be viewed as vectors orthogonal to
each other which together span the whole signal space. In other
words, multiplication of any row of these matrices with an
arbitrary signal vector will give the projection of that arbitrary
vector to that specific row. Additionally, other than the first row
(or column) of the matrices, the number of +1s and -1s at each row
(or column) is equal. Multiplication of the first row, which
corresponds to all 1's, with the position signal samples (i.e., the
signal vector) gives the mean value of that vector. This will, for
example, correspond to the amount of overall base line shift in the
system. Furthermore, since the second row corresponds to
alternating +1's and -1's, multiplication of the second row with
the signal vector will give the amount of the highest frequency
content in signal vector. Significantly, every row of Hadamard
matrix correlates the signal vector with a specific pattern, and
gives an indication how much of that pattern is observed within the
data set. In addition to these properties, one of the rows (or
columns) of the Hadamard matrix corresponds to the servo PS1 and
PS2 field (i.e., the position or read back signal samples) for the
Null Pattern if the number of pulses and number of samples of each
pulse are chosen carefully.
[0051] Referring again to FIG. 7, the PES component extractor 372
is configured to extract a PES component output 378, which
corresponds to the servo burst pattern and is based on the position
signal samples 352. In accordance with one embodiment of the
invention, the PES component 378 is extracted from the transformed
vector {overscore (y)} provided by the transformation block 370. In
general, the PES component 378 corresponds, or is equal to, one of
the components of the vector {overscore (y)}, designated as
{overscore (y)} (n.sub.d)) of the transformed domain
representation. Therefore, the PES component extractor is
configured to complete step 360 of the method.
[0052] The noise extractor 374 is configured to extract a noise
level 380 (N), preferably a dominant noise level, from the
transformed domain representation of the position signal samples
352 (transformed vector {overscore (y)}), to complete step 362 of
the method. In general, the noise components of the transformed
vector {overscore (y)} include all of the components of the vector
{overscore (y)} except the position signal component ({overscore
(y)}(n.sub.d)) of the transformed vector {overscore (y)}. The noise
component of the transformed vector {overscore (y)} having a
maximum absolute value relative to the other noise components
represents the dominant noise level 380 (N). Thus, the noise level
N can be represented as N=max{abs[{overscore (y)}(n)]}, where n is
not equal to n.sub.d.
[0053] The confidence level generator 376 is generally configured
to perform step 364 of the method (FIG. 6) by generating a
confidence level 382 (C) that is indicative of a quality of the PES
component 378 based on the PES component 378 and the noise level
380. The higher the value of the PES component 378 is relative to
the noise level 380, the greater the confidence in the accuracy or
quality of the PES component 378 and the more likely that the PES
component 378 represents useful head position information. As a
result, such PES components 378 are given high confidence
levels.
[0054] An example of the operation of the system will now be
provided using the Hadamard transformation and an assumption that
the number of pulses in each PS field is equal to power of 2 and
the number of samples for each pulse is also equal to power of 2.
Assuming that we have 32 pulses (or 16 servo periods) in each PS
field, and we have 2 samples for each pulse (or 4 samples for each
period), then one servo period will be [1 1 -1 -1], which is
repeated 16 times. We assume that this data is written in PS1, and
half a track width shifted version is written in PS2. If we get the
Hadamard matrix H.sub.64 of length 64, we see that this data
sequence is equal to the 3rd row of H.sub.64. Then, all the PES
component information will be at n.sub.d equal to 3, and the other
components of {overscore (y)}(n) will represent noise. In other
words, the position signal component of the transformed vector
{overscore (y)} (i.e., the PES component 380) will be {overscore
(y)}(3) and the confidence level C will be obtained by comparing
the absolute value of the vector {overscore (y)}(3) with the
maximum absolute value of the other components (i.e., noise
components) of the transformed vector {overscore (y)}.
[0055] Referring again to FIG. 7, one option for the transformation
block 370 is to wait until all of the position signal samples 352
corresponding to each PS field are obtained before transforming
them into the transform domain representation by multiplying the
position signal samples 352 by the corresponding transform matrix H
(e.g., Hadamard transform matrix) to obtain the transformed vector
{overscore (y)}. Thus, for example, the transformation block 370
would have to wait for the whole 64 position signal samples 352
before the transformed vector {overscore (y)} could be obtained.
However, the delay or servo loop latency resulting from such a
configuration would likely be unacceptable.
[0056] FIG. 8 is a block diagram of a portion of the servo control
system in accordance with one embodiment of the invention that
results in more manageable servo loop latency periods. The
transformation block 370 is configured to simultaneously multiply
the correlated position signal samples 352 from the A/D converter
316 with all, or a select number of, the rows h of the transform
matrix H. Each of the rows h of the transform matrix H represent
read back signal noise except row h.sub.d, which corresponds to the
PES component 378. In accordance with one embodiment of the
invention, the transformation block 370 includes a plurality of
multipliers 390 that are each fed a predetermined row h.sub.n (n
represents the row) of the transform matrix H being used (e.g.,
Hadamard transform). The output from each multiplier 390 is summed
with a summing block 392 to obtain the projection of the position
signal samples 352 ({overscore (y)}(n)) onto the particular row
H.sub.n of the transformed matrix H being used to thereby generate
the PES component 378 and the noise components of the transformed
vector {overscore (y)}.
[0057] One embodiment of the noise extractor 374 includes absolute
value blocks 394, which obtain the absolute values of the noise
component of the transformed vector {overscore (y)} received from
the transformation block 370. Additionally, the noise extractor 374
includes a comparator 396. The comparator 396 selects the maximum
of the absolute values of the noise components provided by the
absolute value blocks 394, which is then selected as the dominant
noise level 380 (N). The noise level output 380 is then provided to
the confidence level generator 376.
[0058] The multiplier 390 and the summing block 394 of the
transformation block 370 corresponding to the PES component
extractor 372 produce the position signal component of the
transformed matrix {overscore (y)}, which corresponds to the PES
component 378 of the read back signal. In accordance with one
embodiment of the servo control system, the resultant PES component
378 is provided as an output signal. Additionally, the PES
component is provided to the confidence level generator 376.
[0059] The confidence level generator 376 is configured to
calculate an absolute value of the PES component 378 with absolute
value block 402, which is then provided to a comparator 404. The
dominant noise level 380 (N) is also provided to the comparator
404. The comparator generates the confidence level 382 (C) in
response to a comparison between the PES component 378 and the
noise level 380.
[0060] In accordance with one embodiment of the invention, the
comparison between the PES component 378 and the noise level 380
involves calculating a confidence level ratio M of the absolute
value of the PES component 378 to the noise level 380, as indicated
in Equation 8. M=abs[y(n.sub.d)]/N Eq. 8
[0061] In accordance with one embodiment of the invention, the
confidence level 382 (C) is set based on a comparison of the ratio
M to a threshold value M.sub.max, which can be set empirically.
When M is less than M.sub.max the confidence level C is set to the
ratio M and, otherwise, the confidence level C is set to 1 (or
other constant value), as indicated in Equation 9. Accordingly, the
confidence level will change as a function of the noise amount in
the read back signal of the system. The larger the noise, the lower
the confidence level will be. C level = { M .times. .times. if
.times. .times. M < M max 1 .times. .times. else } Eq . .times.
9 ##EQU8##
[0062] Many alternative methods for calculating the confidence
level C can be also used in accordance with the particular servo
control system or the manner in which it is used.
[0063] Accordingly, one embodiment of the comparator 404 includes
an inverter 406 that inverts the dominant noise level 380. The
output from the inverter 406 is then multiplied by the PES
component 378 using a multiplier 410 to calculate the ratio M,
which is output as a signal 412. A threshold detector 414 then
compares the ratio 412 to a predetermined value 416 (M.sub.max) and
outputs the confidence level 382 (C) according to Equation 9.
[0064] Although the servo loop latency of the servo system of FIG.
8 may be somewhat manageable, it will be complicated due to the
large number of branches in the transformation block 370 that
correspond to the components of the transformed domain
representation (transformed vector {overscore (y)}). Thus, for a
data sequence of length 64, we need 64 branches which means at
least 64 times more complexity compared to the conventional single
branch shown in FIG. 5.
[0065] The complexity of the architecture in FIG. 8 can be
significantly reduced by configuring the transformation block 370
to generate only the components of the transformed vector
{overscore (y)} that are most likely to contain the dominant noise
level 380 and the PES component 378. Some of the branches are easy
to eliminate because they are basically unrelated to read back
signal noise. For example, the branch {overscore (y)}(1)
corresponding to h.sub.1 just takes the sum of the received
position signal samples 352, which means the DC value of the
signal. However, because of the CTF 312 in the system, the DC value
of the signal is removed and, as a result, the branch {overscore
(y)}(1) corresponding to h.sub.1 does not give any useful
information. Similarly, the branch {overscore (y)}(2) corresponding
to h.sub.2 equals alternating +1s and -1s, and again a properly
designed CTF 312 will also filter out most of the energy at this
frequency band. As a result, the complexity of the transformation
block 370 and also the noise extractor 374 can be reduced by
selecting a subset of the transformation matrix rows h.sub.n (e.g.,
Hadamard rows or chips) once the likely dominant noise sources have
been identified for the system in which the servo control system is
utilized, such as a disc drive.
[0066] In accordance with one embodiment of the invention, only one
row h(u) of the transformation matrix H corresponding to the likely
dominant noise component N of the read back signal 310 is selected
to generate the noise component {overscore (y)}(u) of the
transformed vector {overscore (y)}, which will be used as the noise
level. The noise level {overscore (y)}(u)) is provided to the
absolute value block 394 of the noise extractor 374 to generate the
final noise level 380, as shown in FIG. 9. The noise extractor 374,
as shown in FIG. 9. The resultant noise level 380 is then compared
to the PES component 378 as discussed above to generate the
confidence level 382.
Confidence Level Generation Simulation
[0067] In order to provide a more thorough understanding of the
invention, an example of the servo system in operation will be
provided. The pattern utilized in this example will be the Null
Pattern discussed above that consists of 32 pulses (or 16 servo
periods) in each PS field (PS1 and PS2), and we have 2 samples for
each pulse (or 4 samples for each period). Then, one servo period
will be [1 1 -1 -1], and this repeats itself 16 times. We assume
that this data is written in PS1, and half a track width shifted
version is written in PS2.
[0068] The output of the A/D converter 316 in (FIGS. 5 and 9) will
initially be analyzed as a function of an off-track amount. For
this purpose, we choose perpendicular magnetic recording
architecture with normalized density (ND) equal to 1.5 in presence
of only electronic noise of 20 dB. We set the gain of the VGA 306
to be constant, and configure the CTF 312 to be a simple low-pass
filter (LPF). FIG. 10 shows the frequency domain representations of
the sampled noisy read back signal corresponding to PS1 at the
output of the A/D converter 316 as a function of the normalized
frequency for different off-track values. As seen in FIG. 10, the
signal has one dominant tone, and the amplitude of the signal
changes as a function of off-track amount.
[0069] A correlator 340 (shown only in FIG. 5) correlates the read
back signal at the output of the A/D converter 316 with the
dominant tone. The frequency domain representation of the
correlator signal (d(k+.phi.) in FIG. 5 and h.sub.d in FIG. 9) is
shown in FIG. 11. As can be seen, the correlator signal has a peak
at the single tone of the read back signal. Thus, the sum of the
correlator's output will be a very good estimator for the amplitude
of the read back signal at the single tone, thus the amount of
off-track in the system.
[0070] However, there is also noise in the system, and as the
off-track value becomes closer to -0.5 of the track width for PS i
the signal amplitude reduces. This means that the Signal-to-Noise
Ratio (SNR) of the system reduces. Thus, at off-track values where
the signal amplitude is small, the noise in the system will mostly
affect the off-track amount estimation. As a result, the PES
component will likely be of low quality and highly inaccurate most
of the time. The present invention generates additional information
regarding the quality of the extracted PES component in the form of
a confidence level for the PES component, using the method
described above.
[0071] For this example we will utilize the architecture of the
servo system shown in FIG. 9 and the correlator (not shown) of the
upper branch h.sub.u is selected, which has a repetition of [1 1 1
1 -1 -1 -1 -1] which corresponds to the 5th row of the Hadamard
matrix H.sub.64. The frequency domain representation of the noise
correlator h.sub.u is shown in FIG. 12, together with that of
position signal correlator h.sub.d. As discussed above, the
summation of the output of the noise correlator h.sub.u gives us
information about the level of noise in the system. Then, we find
the confidence level C from Equations 8 and 9. In Equation 9,
M.sub.max means how much we want the PES component to be larger
than the noise component for us to be confident about the PES
component or the quality of the PES component.
[0072] With M.sub.max set to 5 (which corresponds to 10
log.sub.10(5).apprxeq.7 dB), 100 servo PS1 and PS2 bursts at 20 dB
of electronic noise for different off-track values are run. FIGS.
13A-13D are plots of confidence levels (vertical axis) for 100
sectors (horizontal axis) corresponding to the PES component of the
PS1 field when the servo system architecture of FIG. 9 is used and
the off-track amounts are -0.50, -0.45, -0.40, and -0.35,
respectively. Similarly, FIGS. 14A-14D are plots of the confidence
levels (vertical axis) for 100 sectors (horizontal axis)
corresponding to the PES component of the PS1 field when the more
complex servo system of FIG. 8 is used and the off-track amounts
are -0.50, -0.45, -0.40, and -0.35, respectively. The mean values
of the 100 confidence levels in FIGS. 13A-13D are 0.29, 0.88, 0.99,
and 1, respectively. Similarly, the mean values of the 100
confidence levels in FIGS. 14A-14D are 0.06, 0.36, 0.74, and 0.95,
respectively.
[0073] Although the confidence level numbers generated by the
simplified servo system architecture of FIG. 9 differ from those
produced by the more complicated architecture of FIG. 8, the trend
is the same. That is, whenever the PES component becomes large
relative to the noise level, the confidence level number increases.
The confidence levels generated by the two systems could be made to
look similar by choosing different M.sub.max numbers for the two
different architectures. Thus, using the simplified servo system
architecture of FIG. 9 may be sufficient for many systems.
[0074] Similar results have been observed for longitudinal
recording channels, as opposed to the perpendicular recording
channels utilized in the above example.
[0075] It is to be understood that even though numerous
characteristics and advantages of various embodiments of the
invention have been set forth in the foregoing description,
together with details of the structure and function of various
embodiments of the invention, this disclosure is illustrative only,
and changes may be made in detail, especially in matters of
structure and arrangement of parts within the principles of the
present invention to the full extent indicated by the broad general
meaning of the terms in which the appended claims are expressed.
For example, the particular elements may vary depending on the
particular application for the method or system of the present
invention while maintaining substantially the same functionality
without departing from the scope and spirit of the present
invention.
[0076] In particular, the description of the present invention
utilized the Null Pattern, as an exemplary servo pattern. The
selection of that servo pattern resulted in the use of the Hadamard
transform as the exemplary transform used to generate the
transformed domain representation (transformed vector {overscore
(y)}) of the position signal samples of the read back signal.
However, it should be understood that confidence levels can be
generated for any servo pattern using its associated transform, as
we can always find the null space of the signal component
corresponding to any given servo pattern. This null space helps us
estimate the amount of noise in the system, from which a noise
level can be generated and compared to the PES component to obtain
the confidence level. Additionally, if tuned accordingly, the
proposed servo system architectures, such as that provided in FIGS.
8 or 9, can also be used to detect dominant noise and/or distortion
effects in the servo system. Thus, other than their usage explained
in this document, the proposed servo system architectures can also
be used for the detection of impurities for either system
characterization and/or to trigger a possible cancellation
algorithm for that specific impurity in the system.
[0077] Furthermore, the method described herein regarding the
generation of the confidence levels is only one of many possible
methods that may be used. For instance, different components of the
servo control system may be utilized to generate the confidence
levels and they may be processed in other blocks of the servo
control system.
[0078] Finally, although the preferred embodiment described herein
is directed to a servo control system for disc drive, it will be
appreciated by those skilled in the art that the teachings of the
present invention can be applied to other control systems, without
departing from the scope and spirit of the present invention.
* * * * *