U.S. patent application number 16/162276 was filed with the patent office on 2020-08-13 for systems and methods for distance independent differential signature detection.
This patent application is currently assigned to Honeywell International Inc.. The applicant listed for this patent is Honeywell International Inc.. Invention is credited to Steven Tin.
Application Number | 20200257878 16/162276 |
Document ID | 20200257878 / US20200257878 |
Family ID | 1000004762629 |
Filed Date | 2020-08-13 |
Patent Application | download [pdf] |
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United States Patent
Application |
20200257878 |
Kind Code |
A1 |
Tin; Steven |
August 13, 2020 |
SYSTEMS AND METHODS FOR DISTANCE INDEPENDENT DIFFERENTIAL SIGNATURE
DETECTION
Abstract
A differential signature detection system is provided. The
system comprises: a target sensor, wherein the target sensor is
configured to measure acoustical signals within a first narrow band
around a target frequency; an offset sensor, wherein the offset
sensor is configured to measure acoustical signals within a second
narrow band around an offset frequency; and a controller coupled to
the target sensor and the offset sensor, wherein the controller is
configured to: compare a signal output of the target sensor with an
output of the signal output of the offset sensor to calculate a
differential measurement that comprises a difference in signal peak
intensity; compare the differential measurement to a reference
signal, wherein the reference signal comprises a threshold
indicative of a presence of a characteristic signature peak
associated with a target object; and produce an output based on the
comparison between the differential measurement and the reference
signal.
Inventors: |
Tin; Steven; (Plymouth,
MN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Honeywell International Inc. |
Morris Plains |
NJ |
US |
|
|
Assignee: |
Honeywell International
Inc.
Morris Plains
NJ
|
Family ID: |
1000004762629 |
Appl. No.: |
16/162276 |
Filed: |
October 16, 2018 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01S 1/72 20130101 |
International
Class: |
G06K 9/00 20060101
G06K009/00; B60W 40/10 20060101 B60W040/10 |
Goverment Interests
U.S. GOVERNMENT LICENSE RIGHTS
[0001] This work was funded in part by the U.S. government under
Government Contract Number HR0011-15-C-0141. The government has
certain rights in the invention.
Claims
1. A differential signature detection system, the system
comprising: at least one target sensor, wherein the at least one
target sensor is configured to measure acoustical signals within a
first narrow band around a target frequency; at least one offset
sensor, wherein the at least one offset sensor is configured to
measure acoustical signals within a second narrow band around an
offset frequency; and a controller coupled to the at least one
target sensor and the at least one offset sensor, wherein the
controller is configured to: compare a signal output of the at
least one target sensor with an output of the signal output of the
at least one offset sensor to calculate a differential measurement
that comprises a difference in signal peak intensity; compare the
differential measurement to a reference signal, wherein the
reference signal comprises a threshold indicative of a presence of
a characteristic signature peak associated with a target object;
and produce an output based on the comparison between the
differential measurement and the reference signal.
2. The system of claim 1, wherein the at least one offset sensor is
further configured to measure a signal peak of at least one offset
frequency by monitoring a narrow band frequency range not including
the at least one target frequency.
3. The system of claim 1, wherein the controller is further
configured to produce a logic output or a binary output as a
function the comparison between the differential measurement and
the reference signal.
4. The system of claim 1, wherein the at least one target sensor
comprises at least a first and second target sensor, wherein the at
least one offset sensor comprises at least a first and second
offset sensor.
5. The system of claim 4, wherein the controller calculates at
least a first differential measurement from the first target sensor
and the first offset sensor, and a second differential measurement
from the second target sensor and the second offset sensor, wherein
the first differential measurement and the second differential
measurement are individually weighted before compared to the
reference signal.
6. The system of claim 5, wherein the first differential
measurement and the second differential measurement are weighted
unequally.
7. The system of claim 1, wherein the at least one target frequency
corresponds to a characteristic signature peak associated with a
vehicle.
8. The system of claim 1, wherein the at least one target sensor
and at least one offset sensor is configured to receive a signal
input from a piezoelectric sensor.
9. The system of claim 1, wherein the controller further comprises:
a target frequency envelope detector coupled to an output of a
first target sensor; an offset frequency envelope detector coupled
to an output of a first offset sensor; wherein the differential
detector determines a difference between an output of the target
frequency envelope detector and an output of the offset frequency
envelope detector to generate a first differential output.
10. The system of claim 1, wherein the at least one target sensor
and at least one offset sensor are tuned to narrow band
detection.
11. The system of claim 1, wherein a perimeter monitoring station
receives the output from the controller.
12. A method for differential signature object identification, the
method comprising: measuring an output signal of at least one
target sensor, wherein the at least one target sensor is configured
to measure acoustical signals within a first narrow band around a
target frequency that corresponds to a signature frequency emitted
by a target object; measuring an output signal of at least one
offset sensor, wherein the at least one offset sensor is configured
to measure acoustical signals within a second narrow band around an
offset frequency; comparing an output signal of the at least one
target sensor with an output signal of the at least one offset
sensor to calculate a differential measurement that comprises a
difference in signal peak intensity; and determining whether the
differential measurement is indicative of a presence of a
characteristic signature peak associated with a target object.
13. The method of claim 12, wherein determining whether the
differential measurement is indicative of a presence of a
characteristic signature peak associated with a target object
comprises: comparing the differential measurement with a reference
signal, wherein the reference signal defines a threshold indicative
of a presence of a characteristic signature peak associated with a
target object, and producing an output based on the comparison
between the differential measurement and the reference signal.
14. The method of claim 12, wherein the at least one offset sensor
is further configured to measure a signal peak of at least one
offset frequency by monitoring a narrow band frequency range not
including the at least one target frequency.
15. The method of claim 12, wherein producing an output based on
the comparison between the difference in the signal peak intensity
and the reference signal further comprises producing a logical or
binary signal output.
16. The method of claim 12, wherein the at least one target sensor
comprises at least a first and second target sensor, wherein the at
least one offset sensor comprises at least a first and second
offset sensor, the method further comprising: calculating at least
a first differential measurement from the first target sensor and
the first offset sensor, and a second differential measurement from
the second target sensor and the second offset sensor, wherein the
first differential measurement and the second differential
measurement are individually weighted before compared to the
reference signal.
17. The method of claim 16, wherein the first differential
measurement and the second differential measurement are weighted
unequally.
18. The method of claim 12, further comprising: transmitting an
indication of a presence of the target object based on determining
whether the differential measurement is indicative of a presence of
a characteristic signature peak associated with the target
object.
19. The method of claim 12, wherein measuring the output signal of
the at least one target sensor further comprises measuring the
signal peak of an at least one frequency corresponding to a
vehicle.
20. The method of claim 12, wherein comparing the output signal of
the at least one target sensor with the output signal of the at
least one offset sensor further comprises the output signal of the
at least one target sensor to be greater than the output signal of
the at least one offset sensor.
Description
BACKGROUND
[0002] The use of passive acoustical sensors is becoming
increasingly present in the fields of object detection and
perimeter monitoring. Such sensors can provide integral data on the
specific properties of an object of interest useful for a variety
of applications, including but not limited to: military threat
detection, highway traffic monitoring, environmental monitoring,
and critical infrastructure protection. Conventional sensors gather
environmental data by receiving input signals and continuously
performing wideband Fast Fourier Transform (FFT) analysis to
determine if the wideband spectrum contains a set of frequencies
unique to the monitored object. While FFT analysis can be
temporally convenient, it is often energy inefficient due to the
large excess of continuous calculations performed from analyzing
unnecessary background noise. This leads to higher maintenance
costs by frequently inspecting or replacing sensors every few
months or fewer. Furthermore, most acoustic sensors are tuned to
detect objects only for a particularized distance and must be
recalibrated each time the sensor is moved, making unattended
sensors of limited use.
[0003] For the reasons stated above and for other reasons stated
below, it will become apparent to those skilled in the art upon
reading and understanding the specification, there is a need for
distance independent differential signature detection.
SUMMARY
[0004] The Embodiments of the present invention provide systems and
methods for object monitoring and will be understood by reading and
understanding the following specification.
[0005] A differential signature detection system is provided. The
system comprises: at least one target sensor, wherein the at least
one target sensor is configured to measure acoustical signals
within a first narrow band around a target frequency; at least one
offset sensor, wherein the at least one offset sensor is configured
to measure acoustical signals within a second narrow band around an
offset frequency; and a controller coupled to the at least one
target sensor and the at least one offset sensor, wherein the
controller is configured to: compare a signal output of the at
least one target sensor with an output of the signal output of the
at least one offset sensor to calculate a differential measurement
that comprises a difference in signal peak intensity; compare the
differential measurement to a reference signal, wherein the
reference signal comprises a threshold indicative of a presence of
a characteristic signature peak associated with a target object;
and produce an output based on the comparison between the
differential measurement and the reference signal.
DRAWINGS
[0006] Embodiments of the present disclosure can be more easily
understood and further advantages and uses thereof more readily
apparent, when considered in view of the description of the
preferred embodiments and the following figures in which:
[0007] FIG. 1 is a diagram illustrating an object detection system
of one embodiment of the present disclosure using differential
measurement detection.
[0008] FIGS. 2A and 2B are diagrams illustrating operation of an
object detection system of one embodiment of the present
disclosure.
[0009] FIG. 3 is a diagram of a single target frequency
differential measurement detector for a as presented in one
embodiment of the present disclosure.
[0010] FIG. 4 is a diagram illustrating a multiple target
frequencies object detection system as presented in one embodiment
of the present disclosure.
[0011] FIG. 5 is a diagram of another multiple target frequencies
object detection system as presented in one embodiment of the
present disclosure.
[0012] FIG. 6 is flow charts which illustrates a method for one
embodiment of the present disclosure.
[0013] FIG. 7 is a diagram which illustrates a method for one
embodiment of the present disclosure.
[0014] In accordance with common practice, the various described
features are not drawn to scale but are drawn to emphasize features
relevant to the present disclosure. Reference characters denote
like elements throughout figures and text.
DETAILED DESCRIPTION
[0015] In the following detailed description, reference is made to
the accompanying drawings that form a part hereof, and in which is
shown by way of specific illustrative embodiments in which the
embodiments may be practiced. These embodiments are described in
sufficient detail to enable those skilled in the art to practice
the disclosed embodiments, and it is to be understood that other
embodiments may be utilized and that logical, mechanical, and
electrical changes may be made without departing from the scope of
the present disclosure. The following detailed description,
therefore, is not to be taken in a limiting sense.
[0016] Embodiments of the present disclosure provide systems and
methods for object detection using differential signal detection.
As further described below, the embodiments herein facilitate low
power consumption and detection of objects independent of the
distance of the detector from that object. The embodiments
presented herein thus allow the use of minimal power upkeep costs,
potentially at the nanoWatt (nW) level, for a sensor in an active
detection state while simultaneously allowing continuous
environmental monitoring. The maintenance costs are further reduced
by calibrating the sensor to reliably detect a target object for
all available detection distances, thus mitigating the costs of
recalibrating the sensor for each respective distance from the
target object. In one embodiment, a target sensor is used in
conjunction with a companion offset sensor whose measurements are
compared to derive a differential measurement. In another
embodiment, the output of the grouped sensors are further weighted
to compare against a predetermined reference threshold.
[0017] FIG. 1 is a block diagram illustrating differential
signature object detection system 100 of one embodiment of the
present disclosure. In the embodiment shown in FIG. 1, system 100
comprises at least one target sensor 102, at least one offset
sensor 104, and a controller 106. The target sensor 102 and offset
sensor 104 can comprise any device that measures environmental
signals of interest, such as acoustical signals. In some
embodiments, the target sensor 102 and offset sensor 104 can also
be implemented with piezoelectric materials. In some embodiments,
controller 106 comprises a processor 110 coupled to a memory
storage unit 114 that executes code in order to perform one or more
of the functions of the controller 106 described herein. In some
embodiments, the weights for the target frequencies may be stored
within memory storage unit 114. In some embodiments, target sensor
102, and offset sensor 104 each comprise narrow band acoustical or
vibration energy sensors, such as but not limited to microphones,
vibration sensors, and other devices that measure acoustical waves.
With embodiments of the present disclosure, measurements from
target sensor 102 and offset sensor 104 are compared in order to
obtain a differential signature measurements. This configuration
for obtaining differential signature measurements eliminates the
need for performing FFT calculations, or other processing intensive
algorithms, to determine when frequency peaks indicative of an
object of interest are being received.
[0018] The inputs from the target sensor 102 and offset sensor 104
are sent to the controller 106. The target sensor 102 and offset
sensor 104 are designed to monitor only narrow band frequency
ranges. The processor 110 may perform additional processing
functions as needed to identify the relevant target frequencies,
such as signal enhancement or filtration. In some embodiments, the
processor 110 can be a separate entity that receives input signals
from the target sensor 102 or offset sensor 104; however, in other
embodiments the processor 110 can be located within the target
sensor 102 or offset sensor 104 itself. Additionally, the
controller 106 may contain an interface unit 112. The interface
unit 112 allows user input for a variety of system functions,
including but not limited to: post-wideband spectrum processing,
distance calibration adjustments, and reference threshold
adjustments.
[0019] FIGS. 2A and 2B illustrate operation of a differential
signature detection system, such as the system 100 shown in FIG. 1.
As shown in FIG. 2A, the target sensor 102 may be calibrated to
detect objects that emit acoustical energy characterized by a
target frequency signature comprising spikes or peaks at certain
frequencies. For example, FIG. 2A illustrates acoustical energy
measured by target sensor 102 over a narrow band spectrum. Narrow
band spectral monitoring as described herein is defined as
frequencies within <1% of the selected target frequency. The
presence of acoustical energy received at frequency f.sub.target
(shown at 204) in excess of a threshold value 202 indicates that
acoustic energy having a frequency within a spectrum associated
with an object of interest has been received. In the particular
implementation shown in FIG. 2A, an example target frequency
signature f.sub.target of 55.5 Hz is used for illustrative purposes
only. In other embodiments, other target frequencies may be used,
the selection of which would be based on the target object that
needs to be detected. However, merely establishing a threshold
setting 202 based on an absolute measurement of acoustical energy
received by target sensor 102 to discern whether an object of
interest is present may result in either false positive detection
or missed detections. FIG. 2A shows that as the target is further
away from the sensors where the signature signal strength at 55.5
Hz decreases. When the target is 10 meters away from the sensor,
although there exists a large signal-to-noise ratio correlating a
strong likelihood of the presence of the target object at the
observed characteristic signature peak of the desired target 204,
but the observed characteristic signature peak levels below the
threshold 202, a missed detection occurs. A false positive may be
triggered in a noisy environment that produces another signal
(usually wide-band) falling within the frequency band monitored by
target sensor 102 with sufficient energy to meet the threshold 202.
As an example for false positives, as shown in FIG. 2A, another
signal with sufficient energy to meet threshold 202, could produce
a false positive.
[0020] As opposed to relying on detection of absolute threshold
levels, system 100 implements a differential detector that measures
the differences between signals received from the target sensor 102
and the offset sensor 104, which may be used to detect the
existence of a received characteristic signature peak 204,
regardless of the distance between the sensor and the target object
and the presence of interfering ambient noise.
[0021] Because target sensor 102 is tuned to a narrow spectral
band, it receives the signal data at a width that captures the peak
204 and other signals within that band. Offset sensor 104, is also
tuned to a narrow spectral band, but that band is slightly offset
from the band of the target sensor so that it does not also measure
the target frequency at peak 204. In the particular implementation
shown in FIG. 2B, an example offset frequency signature foffset of
53.5 Hz is used for illustrative purposes only. In other
embodiments, other offset frequencies may be used, the selection of
which would be based on the target object that needs to be
detected. As an example, FIG. 2B shows an offset sensor tuned to
53.5 Hz to compare to a target sensor tuned to 55.5 Hz. The offset
sensor 104 therefore functions to measure the ambient acoustic
energy level within the immediate proximity of the target sensor
102, so that a differential measurement between the two sensors can
be obtained, as shown in FIG. 2B. If the target sensor 102 produces
a first measurement of acoustic energy, and the offset sensor 104
produces a second measurement of acoustic energy that is the same,
or approximately the same at the first measurement, then the
differential measurement (meaning the difference obtained by
subtracting the second measurement from the first measurements)
will be small. This would be an indication of that the
characteristic signature peak 204 of interest has not be detected.
In contrast, if the target sensor 102 produces a first measurement
of acoustic energy, and the offset sensor 104 produces a second
measurement of acoustic energy that is substantially less than the
first measurement, then the differential measurement will not be
small. In that case, if the differential measurement obtained
exceeds a threshold, then that is an indication that a spike such
as the characteristic signature peak 204 has been received. This
indication may then be evaluated, as discussed below, to determine
if the approach of a target object has been detected.
[0022] In the embodiment shown in FIG. 1, a single offset sensor
pair is utilized, comprising a target sensor 102 and offset sensor
104. This embodiment may be useful, for example, when a single
target frequency can be used to distinguish a target object from
other objects. A differential detector 108 is used to compare the
amplitude of the signal at the target frequency with the amplitude
at the offset frequency to determine the difference in signal peak
intensity of the two frequencies as discussed in FIG. 3 below. The
output 118 of the controller 106 may be sent to a perimeter
monitoring station to trigger additional functions, such as opening
a communications channel or to activate security protocols.
[0023] FIG. 3 is a block diagram illustrating a differential
detector 300 used in at least one embodiment in the present
disclosure, such as the differential detector 108 of FIG. 1. As
described above, the target sensor 102 is used to monitor the
narrow band of a target frequency while offset sensor 104 is used
to monitor the narrow band range of a frequency just outside the
target frequency. The signals from both sensors 102 and 104 are
input into the differential detector 300. The signals from the
target sensor 102, and the offset sensor 104, are each further
processed by respective envelope detectors 306 and 308. The
envelope detector 306 outputs envelope signal generated from the
signal peak of the signal from the target sensor 102. The envelope
detector 308 outputs envelope signal generated from the signal peak
of the signal from the offset sensor 104. The outputs from these
envelope detector 308 provide cleaner signals for comparison than
the original signal. In one embodiment, the signal outputs from the
envelope detectors 306 and 308 are input to a difference calculator
309 to produce the differential measurement output. In one example
embodiment, the difference calculator 309 may comprise a negative
weighted multiplier at one of its inputs, to invert the amplitude
of the signal from offset sensor 104 and then a signal combiner 310
sums up the two signals to produces an output indicative of the
difference between in signal peak intensity at the target and
offset frequencies. The functions of the negative weighted
multiplier and combiner 310 may be realized by a single device, for
example by implementing a differential amplifier. The output from
difference calculator 309 is an analog voltage signal, which can be
compared to a threshold reference signal in a comparator 312. The
threshold reference signal may be set at a voltage level where a
greater signal peak intensity would set a positive identification
of the target object, and conversely, where a lower signal peak
intensity would set a confirmed absence of the target object. The
threshold reference signal amplitude can be adjusted to change the
sensitivity of the detection system to characteristic peak 204.
[0024] In another embodiment, multiple offset sensor pairs, each
comprising target sensors and offset sensors such as shown and
described in FIGS. 1-3, are used when the acoustical spectrum of
the target object from wideband data gathering reveals several
target frequencies to be monitored. FIG. 4 describes such an
embodiment. To illustrate the use of monitoring several target
frequencies, three target sensors 402, 406, and 410 are shown.
However, this example is meant to be illustrative only as other
implementations of this embodiment may include any number of target
and offset sensors. In FIG. 4, each combination of target sensors
402, 406, and 410 and offset sensors 404, 408, and 412 is tuned to
a particular target frequency band, based on a set of multiple
characteristic signature peaks 204 associated with the objected
targeted for detection.
[0025] For example, a broadband spectral measurement of a target
object can be obtained, and an FFT spectral analysis performed to
establish the set of characteristic signature peaks that are
associated with that object. For each characteristic signature
peaks established by the spectral analysis, there would be an
associated offset sensor paid comprising a target sensor tuned to
the corresponding target frequency, and an offset sensor, tuned to
be offset from that corresponding target frequency. For example, if
a FFT spectral analysis of a target object established
characteristic signature peaks at 67 Hz, 108 Hz, and 134 Hz, then
three groups of target sensors and offset sensors could be used,
for example, with target sensor 402 tuned to 67 Hz, target sensor
406 tuned to 108 Hz, and target sensor 410 turned to 134 Hz.
Accordingly, offset sensor 404 would be tuned to a frequency offset
from 67 Hz, offset sensor 408 would be tuned to a frequency offset
from 108 Hz, and offset sensor 412 would be tuned to a frequency
offset from 134 Hz. A differential comparison of each target sensor
402, 406, and 410 and offset sensor 404, 408, and 412 combination
is performed using a separate differential detector 418 for each
offset sensor pair.
[0026] As shown in FIG. 4, in some embodiments, the functions of
the differential detector 418 may be implemented by a controller
414 comprising a processor 419 coupled to, or otherwise comprising,
a memory storage unit 420. The processor may execute code stored in
the memory 420 to implement a weighting function 421 that evaluates
the outputs of the separate differential detector 418 to make the
determination of whether a target object has been detected. That
is, a set of weighting factor 422 is stored in the memory 240, and
each weighting factor is applied to the output of one of the
differential detector 418 and the results processed to determine
when a target object has been detected.
[0027] FIG. 5 is a block diagram of a differential output weighting
function 500 such as the weighting function 421 describe in FIG. 4,
where multiple target frequencies, each associated with a
characteristic signature peak, are obtained from the acoustical
spectrum of the target object. The initial inputs 502 comprise the
difference in signal peak intensity from each offset sensor pairs
as output from the differential detectors 418. The weighting factor
422 are predetermined values calculated by an algorithm that takes
into account various factors, including but not limited to: the
number of target frequencies, the magnitude of the differential
output signal, and the acoustical characteristics of the target
object. Each output from a differential detector 418 is multiplied
by one of the weighting factor 422 to obtain a set of weighted
differential signals (shown at 504).
[0028] The weighted differential signals 504 are combined by the
weighting function 500 using a weighted classifier 506. The
weighted classifier 506 may combine all weighted frequency signals
in a linear fashion, or in other embodiments, may combine them in a
non-linear fashion e.g. if a particular target frequency is known
to be more probative of identifying the target object than another.
The output of the weighted classifier 506 may then be compared to a
reference signal 508 to determine if a target object has been
detected. The reference signal 508 can be determined based on an
algorithm that considers various factors, such as the strength of
the background noise and the variance in noise fluctuation. The
final output 510 can be converted to a logical or binary output via
an analog-to-digital converter as described above.
[0029] FIG. 6 is a flow chart depicting a method 600 of identifying
an object independent of distance using a differential output
measurement of one embodiment of the present disclosure. This
method 600 can be implemented, for example, via the single target
frequency system 100 described above. The method begins at block
602, where a target sensor tuned to a particular target frequency
measures an environmental signal, such as an acoustical signal.
Specifically, the target sensor 102 is tuned to detect the
magnitude of environmental signals over a narrow range around the
target frequency. In some embodiments, the target sensor 102 is
calibrated to detect an object genus, rather than a particular
species. For example, if the invention is used in the field of
vehicle detection, a sensor may be tuned to recognize the
characteristic signature peak that is common to a range of vehicles
(such as pickup trucks, for example), rather than the more specific
vehicle model (such as a Ford F-150, for example). Of course, it is
to be understood by one skilled in the art that the size of the
class monitored is dependent on the sensitivity of the sensor used.
Furthermore, some classes would require analyzing multiple target
frequencies, which is discussed in another embodiment below. At
block 604, the method proceeds by measuring an output signal of a
separate offset sensor 104 tuned to a narrow band around an offset
frequency, as described above. That is, the offset sensor 104 may
be calibrated to measure environmental signals of a frequency just
outside the known target frequency that corresponds to the
monitored object. The selection of an appropriate offset frequency
band may be based on several factors, including but not limited to,
the nature of the object monitored, the magnitude and variation of
the background noise signals, and the sensitivity of the sensor.
For example, in some embodiments, the center frequency of the
offset sensor may be offset from the center frequency of the target
sensor on the order of 2-3 Hz.
[0030] Proceeding to block 606, the method comprises comparing an
output signal of the at least one target sensor with an output
signal of the at least one offset sensor to calculate a
differential measurement that comprises a difference in signal peak
intensity. For example, a difference in signal peak intensity of
the environmental signals measured by the target 102 and offset 104
sensors may be determined. In some embodiments, the signals from
the target and offset sensors are each input into an envelope
detector, which generates the envelope of the combined
wavelets.
[0031] The method then proceeds to block 608, with determining
whether the differential measurement is indicative of a presence of
a characteristic signature peak associated with a target object. In
some embodiments, this may include comparing the differential
measurement to a threshold level. In one embodiment, to trigger a
positive result at block 610, an absolute value of the difference
in signal peak intensity is greater than the absolute value of the
threshold level. Likewise, a negative result may be triggered when
the absolute value of the signal peak intensity is less than the
reference signal.
[0032] FIG. 7 is a flow chart depicting a method 700 of identifying
an object using a plurality of characteristic signature peak of a
target object. Method begins at 710 with obtaining a plurality of
differential measurements from a plurality of offset sensor pairs,
each offset sensor pair associated with detecting a different
characteristic signature peak. In some embodiments, each
differential measurement may be obtained in the manner described
above with respect to FIG. 6.
[0033] The method proceeds to 720 where each plurality of
differential measurements are individually weighted using weighting
factors to produce a plurality of weighted differential
measurements. In some embodiments, the signals can be weighted by
multiplying the differential measurement by weighting factor
derived from one or more factors, including but not limited to the
amount of target frequencies monitored and the signal-to-noise
ratio. In some embodiments, each weighted difference is weighted
based on a linear classifier. In other embodiments, a non-linear
weighing system may be used.
[0034] The method proceeds to 730 where the weighted differential
measurements are summed to obtain a single weighted signal output,
which may comprise one or more statistical techniques that would be
known to those skilled in the art. The weighted signal output is
then compared to a reference threshold at 740 to determine whether
the weighted signal output is indicative of a presence of a
characteristic signature peak associated with a target object.
[0035] In any of the embodiments described herein, the
determination of whether the presence of a target object is
detected may be used to trigger transmitting an indication of the
presence of the target object, such as to a perimeter monitoring
station or for other purposes such as triggering external
functions, alarms, or activation of security protocols, for
example.
Example Embodiments
[0036] Example 1 includes a differential signature detection system
comprising: at least one target sensor, wherein the at least one
target sensor is configured to measure acoustical signals within a
first narrow band around a target frequency; at least one offset
sensor, wherein the at least one offset sensor is configured to
measure acoustical signals within a second narrow band around an
offset frequency; and a controller coupled to the at least one
target sensor and the at least one offset sensor, wherein the
controller is configured to: compare a signal output of the at
least one target sensor with an output of the signal output of the
at least one offset sensor to calculate a differential measurement
that comprises a difference in signal peak intensity; compare the
differential measurement to a reference signal, wherein the
reference signal comprises a threshold indicative of a presence of
a characteristic signature peak associated with a target object;
and produce an output based on the comparison between the
differential measurement and the reference signal.
[0037] Example 2 includes the system of example 1, wherein the at
least one offset sensor is further configured to measure a signal
peak of at least one offset frequency by monitoring a narrow band
frequency range not including the at least one target
frequency.
[0038] Example 3 includes the system of any of examples 1-2,
wherein the controller is further configured to produce a logic
output or a binary output as a function the comparison between the
differential measurement and the reference signal.
[0039] Example 4 includes the system of any of examples 1-3,
wherein the at least one target sensor comprises at least a first
and second target sensor, wherein the at least one offset sensor
comprises at least a first and second offset sensor.
[0040] Example 5 includes the system of example 4, wherein the
controller calculates at least a first differential measurement
from the first target sensor and the first offset sensor, and a
second differential measurement from the second target sensor and
the second offset sensor, wherein the first differential
measurement and the second differential measurement are
individually weighted before compared to the reference signal.
[0041] Example 6 includes the system of example 5, wherein the
first differential measurement and the second differential
measurement are weighted unequally.
[0042] Example 7 includes the system of any of examples 1-6,
wherein the at least one target frequency corresponds to a
characteristic signature peak associated with a vehicle.
[0043] Example 8 includes the system of any of examples 1-7,
wherein the at least one target sensor and at least one offset
sensor is configured to receive a signal input from a piezoelectric
sensor.
[0044] Example 9 includes the system of any of examples 1-8,
wherein the controller further comprises: a target frequency
envelope detector coupled to an output of a first target sensor; an
offset frequency envelope detector coupled to an output of a first
offset sensor; wherein the differential detector determines a
difference between an output of the target frequency envelope
detector and an output of the offset frequency envelope detector to
generate a first differential output.
[0045] Example 10 includes the system of any of examples 1-9,
wherein the at least one target sensor and at least one offset
sensor are tuned to narrow band detection.
[0046] Example 11 includes the system of any of examples 1-10,
wherein a perimeter monitoring station receives the output from the
controller.
[0047] Example 12 includes a method for differential signature
object identification comprising: measuring an output signal of at
least one target sensor, wherein the at least one target sensor is
configured to measure acoustical signals within a first narrow band
around a target frequency that corresponds to a signature frequency
emitted by a target object; measuring an output signal of at least
one offset sensor, wherein the at least one offset sensor is
configured to measure acoustical signals within a second narrow
band around an offset frequency; comparing an output signal of the
at least one target sensor with an output signal of the at least
one offset sensor to calculate a differential measurement that
comprises a difference in signal peak intensity; and determining
whether the differential measurement is indicative of a presence of
a characteristic signature peak associated with a target
object.
[0048] Example 13 includes the method of example 12, wherein
determining whether the differential measurement is indicative of a
presence of a characteristic signature peak associated with a
target object comprises: comparing the differential measurement
with a reference signal, wherein the reference signal defines a
threshold indicative of a presence of a characteristic signature
peak associated with a target object, and producing an output based
on the comparison between the differential measurement and the
reference signal.
[0049] Example 14 includes the method of any of examples 12-13,
wherein the at least one offset sensor is further configured to
measure a signal peak of at least one offset frequency by
monitoring a narrow band frequency range not including the at least
one target frequency.
[0050] Example 15 includes the method of any of examples 12-14,
wherein producing an output based on the comparison between the
difference in the signal peak intensity and the reference signal
further comprises producing a logical or binary signal output.
[0051] Example 16 includes the method of any of examples 12-15,
wherein the at least one target sensor comprises at least a first
and second target sensor, wherein the at least one offset sensor
comprises at least a first and second offset sensor, the method
further comprising: calculating at least a first differential
measurement from the first target sensor and the first offset
sensor, and a second differential measurement from the second
target sensor and the second offset sensor, wherein the first
differential measurement and the second differential measurement
are individually weighted before compared to the reference
signal.
[0052] Example 17 includes the method of example 16, wherein the
first differential measurement and the second differential
measurement are weighted unequally.
[0053] Example 18 includes the method of any of examples 12-17,
further comprising: transmitting an indication of a presence of the
target object based on determining whether the differential
measurement is indicative of a presence of a characteristic
signature peak associated with the target object.
[0054] Example 19 includes the method of any of examples 12-18,
wherein measuring the output signal of the at least one target
sensor further comprises measuring the signal peak of an at least
one frequency corresponding to a vehicle.
[0055] Example 20 includes the method of any of examples 12-19,
wherein comparing the output signal of the at least one target
sensor with the output signal of the at least one offset sensor
further comprises the output signal of the at least one target
sensor to be greater than the output signal of the at least one
offset sensor.
[0056] In various alternative embodiments, system elements, method
steps, or examples described throughout this disclosure (such as
the controller, differential output weighting function,
differential detectors and/or sub-parts thereof, for example) may
be implemented using one or more computer systems, field
programmable gate arrays (FPGAs), or similar devices and/or
comprising a processor coupled to a memory and executing code to
realize those elements, processes, steps or examples, said code
stored on a non-transient data storage device. Therefore other
embodiments of the present disclosure may include elements
comprising program instructions resident on computer readable media
which when implemented by such computer systems, enable them to
implement the embodiments described herein. As used herein, the
term "computer readable media" refers to tangible memory storage
devices having non-transient physical forms. Such non-transient
physical forms may include computer memory devices, such as but not
limited to punch cards, magnetic disk or tape, any optical data
storage system, flash read only memory (ROM), non-volatile ROM,
programmable ROM (PROM), erasable-programmable ROM (E-PROM), random
access memory (RAM), or any other form of permanent,
semi-permanent, or temporary memory storage system or device having
a physical, tangible form. Program instructions include, but are
not limited to computer-executable instructions executed by
computer system processors and hardware description languages such
as Very High Speed Integrated Circuit (VHSIC) Hardware Description
Language (VHDL).
[0057] Although specific embodiments have been illustrated and
described herein, it will be appreciated by those of ordinary skill
in the art that any arrangement, which is calculated to achieve the
same purpose, may be substituted for the specific embodiment shown.
This application is intended to cover any adaptations or variations
of the present disclosure. Therefore, it is manifestly intended
that embodiments be limited only by the claims and the equivalents
thereof.
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