Title: Method and apparatus for the extraction and compression of surveillance information to facilitate high performance data fusion in distributed sensor systems
Abstract: A method and apparatus for the generic extraction and compression of surveillance information that facilitates high performance data fusion in distributed sensor systems. According to the method, multiple sensors (120[1] . . . 120[N]), distributed over a wide surveillance area (100), sense surveillance data of interest (310), optionally filter that sensed data (340), extract non-essential data (360) from the filtered data, compress in a manner specific to the extracted data (370) the extracted data for transmission and subsequently transmit (380) the compressed data to a "master" processing system (220) for integration/fusion with other transmitted compressed data streams originating from other sensors. Reductions in required data transmitted is on the order of 100:1.
Patent Number: 7,005,981 Issued on 02/28/2006 to Wade
| Inventors:
|
Wade; Robert (Branchville, NJ)
|
| Assignee:
|
The United States of America as represented by the Secretary of the Army (Washington, DC)
|
| Appl. No.:
|
709724 |
| Filed:
|
May 25, 2004 |
| Current U.S. Class: |
340/539.17; 340/539.16 |
| Current Intern'l Class: |
G08B 1/08 (20060101); H04Q 7/00 (20060101) |
| Field of Search: |
340/53917,539.16,539.18,539.22,541
375/240
|
References Cited [Referenced By]
U.S. Patent Documents
Primary Examiner: Tweel, Jr.; John
Attorney, Agent or Firm: Moran; John F.
Parent Case Text
CROSS REFERENCE TO RELATED APPLICATIONS
This application claims benefit under 35 USC 199(e) of provisional application
60/320,223, filed May 27, 2003, the entire file wrapper contents of which provisional
application are herein incorporated by reference as though fully set forth at length.
Claims
What is claimed is:
1. In a surveillance system comprising a master processing system and one or
more sensor systems, said sensor systems being distributed throughout a surveillance
area and in communications with the master processing system, a surveillance method
comprising the steps of:
at the master processing system:
receiving data streams from the sensor systems;
analyzing the received data streams to determine characteristics of a target
situated within the surveillance area; and
repeating the above receiving and analyzing steps; and
at the sensor systems:
collecting sensor specific stimulus (data);
pre-processing the collected data;
applying a matched extraction/compression scheme to the pre-processed data; and
transmitting the extracted/compressed data to the master processing system.
2. The method according to claim 1 wherein the applying step comprises the steps of:
extracting non-essential information from the preprocessed data; and
compressing using a compression scheme that is matched to the extraction, the
pre-processed data having the non-essential information extracted.
3. The method according to claim 2, further comprising the steps of:
at the master processing system:
determining, based upon the analysis, whether additional information is to be
provided by master processing system to a sensor system; and
sending, based upon the determination, any additional information from the master
processing system to the sensor system.
4. The method according to claim 1 wherein the transmitting from the sensor system
to the master processing system is performed via a wireless communications link.
5. The method according to claim 1, wherein each of the sensor systems include
a sensor, responsive to sensor specific stimulus, said sensor being one selected
from the group consisting of: acoustic, magnetic, seismic, chemical, and photonic sensors.
6. The method according to claim 2 wherein said extraction and compression steps
result in at least a 100:1 reduction in data.
7. The method according to claim 1 wherein said pre-processing step includes
the step of:
converting, from an analog domain to a digital domain through the action of an
analog/digital converter, the sensor specific data.
8. The method according to claim 3 wherein said determination is made as a result
of a particular type of target surveiled.
9. The method according to claim 2 further comprising the steps of:
generating a sparse array of sensor systems from the one or more sensor systems
distributed throughout the surveillance area.
10. The method according to claim 9 further comprising the steps of:
modifying the sparse array of sensor systems such that a new sparse array is
generated from the one or more sensor systems distributed throughout the surveillance area.
11. Apparatus for the generic extraction and compression of information for surveillance
to facilitate high performance data fusion in distributed sensor systems, said
apparatus comprising:
a master processing system for receiving and processing one or more data streams
transmitted from one or more respective sensor systems distributed throughout a
surveillance area; and
one or more sensor systems including:
a sensor, responsive to sensor-specific stimulus, producing a raw sensor data signal;
a pre-processor for processing the raw sensor data signal;
a matched extractor/compressor for further processing the pre-processed signal;
a transmitter for transmitting the further processed signal to the master processing system.
12. The apparatus according to claim 11 wherein the pre-processor further comprises:
an analog/digital converter for converting analog raw sensor data signal to a
digital signal representative of the raw sensor data.
13. The apparatus according to claim 12 wherein the pre-processor further comprises:
one or more filters, for conditioning the digital signal.
14. The apparatus according to claim 13, wherein the extractor/compressor includes:
an extraction module for extracting non-essential information from the conditioned
digital signal; and
a compression module for compressing the data signal having the non-essential
information extracted;
wherein the matched extraction/compression is optimally matched to the specific
sensor type.
15. The apparatus according to claim 14 wherein the transmitter is a wireless transmitter.
16. The apparatus according to claim 15 wherein each of the sensor systems include
a sensor selected from the group consisting of: acoustic, magnetic, seismic, chemical,
and photonic sensors.
17. The apparatus according to claim 15 wherein the extractor/compressor produces
at least a 100:1 reduction in data volume for transmission.
Description
FEDERAL RESEARCH STATEMENT
The inventions described herein may be manufactured, used and licensed by or
for the U.S. Government for U.S. Government purposes.
BACKGROUND OF INVENTION
1. Field of the Invention
This invention relates generally to the surveillance of one or more objects
over a surveillance area. More particularly, it relates to methods and apparatus
for the generic extraction and compression of surveillance data acquired from multiple
sensors operating over a surveillance area that facilitate the fusion of such data
into more useful or otherwise actionable information.
2. Background of the Invention
Multi-sensor surveillance systems and methods are receiving significant
attention for both military and nonmilitary applications due, in part, to a number
of operational benefits provided by such systems and methods. In particular, some
of the benefits provided by multi-sensor systems include: Robust operational performance
is provided because any one particular sensor of the multi-sensor system has the
potential to contribute information while others are unavailable, denied (jammed),
or lacking coverage of an event or target; Extended spatial coverage is provided
because one sensor can "look" where another sensor cannot; Extended temporal coverage
is provided because one sensor can detect or measure at times that others cannot;
Increased confidence is accrued when multiple independent measurements are made
on the same event or target; Reduced ambiguity in measured information is achieved
when the information provided by multiple sensors reduces the set of hypothesis
about a target or event; Improved detection performance results from the effective
integration of multiple, separate measurements of the same event or target; Increased
system operational reliability may result from the inherent redundancy of a multi-sensor
suite; and Increased dimensionality of a measurement space (i.e., different sensors
measuring various portions of the electro-magnetic spectrum) reduces vulnerability
to denial (countermeasures, jamming, weather, noise) of any single portion of the
measurement space.
These benefits, however, do not come without a price. The overwhelming volume
and complexity of the disparate data and information produced by multi-sensor systems
is well beyond the ability of humans to process, analyze and render decisions in
a reasonable amount of time. Consequently, data fusion technologies are being developed
to help combine various data and information structures into form(s) that are more
convenient and useful to human operators.
Briefly stated, data fusion involves the acquisition, filtering, correlation
and integration of relevant data and/or information from various sources, such
as multi-sensor surveillance systems, databases, or knowledge bases into one or
more formats appropriate for deriving decisions, system goals (i.e., recognition,
tracking, or situation assessment), sensor management or system control. The objective
of data fusion is the maximization of useful information, such that the fused information
provides a more detailed representation with less uncertainty than that obtained
from individual source(s). While producing more valuable information, the fusion
process may also allow for a more efficient representation of the data and may
further permit the observation of higher-order relationships between respective
data entities.
Current systems and methods for multi-sensor surveillance have typically
utilized sensor platforms or "node level solutions" that employ relatively powerful
processors to determine the bulk of a target classification and tracking solution
at a local surveillance node level. Typical sensor data fusion approaches in distributed
sensor systems are low performance, and could be more accurately described as systems
that share "pre-processed" data generated at the node level (such as target classification,
range, or bearing).
There is a tendency to design system solutions in this manner in order to reduce
the data transmission requirements between nodes or from the nodes to a central
processor. Such system approaches have been difficult to develop and are not inherently
flexible because of constant upgrades to node level processing and custom system
level data fusion, which is inextricably related to custom hardware/software within
the node. Accordingly, efficient data collection and high performance data fusion
has not been realized in distributed sensor systems as a result of the inability
to define a suitably flexible system solution and the inability to collect all
sensor information from multiple sensor sites. Accordingly, systems and methods
that provide multi-sensor surveillance, while simultaneously facilitating the data
fusion from these sensors, are of great interest.
SUMMARY OF INVENTION
Such systems and methods that provide a highly flexible and efficient solution
for collecting and transmitting sensor information from multiple sensors and multiple
sensor types within a surveillance area, while simultaneously facilitating the
theoretical limits of data fusion, are the subject of the present invention.
Viewed from a first aspect, the present invention describes methods for the
generic extraction and compression of surveillance information, whereby multiple
sensors, distributed over a wide surveillance area, sense surveillance data of
interest, optionally filter that sensed data, extract non-essential data from the
filtered data, compress in a manner specific to the extracted data the extracted
data for transmission and subsequently transmit the compressed data to a "master"
processing system for integration/fusion with other transmitted compressed data
streams originating from other sensors.
Advantageously, the methods of the present invention are applicable
to a wide variety of sensor types and data including: acoustic, seismic, magnetic,
electro-magnetic, chemical or other types of sensors, either alone or in combination
with like or unlike sensors. Additionally, as the methods provide a significant
savings in communications requirements, they are applicable to a very large number
of sensor(s) and sensor type(s), distributed across a wide geographic surveillance
area. As a result, multi-sensor surveillance systems incorporating the methods
will be highly scalable, thereby driving their applicability to a wide array of
surveillance problems, while facilitating the potential for new and innovative
data fusion techniques to be applied.
Viewed from another aspect, the present invention is directed to a system
comprising multiple sensor-systems in communication with a master processing system.
The sensor systems may be geographically remote to the master processing system.
The sensor systems further include a sensor, for sensing surveillance data of interest,
a filter for filtering the sensed surveillance data, and an extractor/compressor
by which the filtered data has non-essential data extracted prior to compression
by the compressor and subsequent transmission via a transmitter to the master processing system.
The master processing system receives the transmitted data from multiple sensors
distributed throughout the surveillance area for integration/analysis/fusion and
subsequent action.
BRIEF DESCRIPTION OF DRAWINGS
Various features and advantages of the present invention and the manner of
attaining them will be described in greater detail with reference to the following
description, claims and drawing in which reference numerals are reused—where
appropriate—to indicate a correspondence between the referenced items, and wherein:
FIG. 1 is a schematic illustration of a surveillance area including a number
of sensors according to the present invention;
FIG. 2 is a schematic illustration of a surveillance system according to the
present invention;
FIG. 3 is a block diagram of a generic sensor system according to the present invention;
FIG. 4A is a flowchart depicting a sensory method operating in a sensor system,
according to the present invention; and
FIG. 4B is a flowchart depicting a processing method operating in a master processing
system in conjunction with the method depicted in FIG. 4A, and according to the
present invention.
DETAILED DESCRIPTION
FIG. 1 is a schematic illustration of a surveillance area that will serve as
a starting point for a discussion of the present invention. In particular, and
with reference to that FIG. 1, there is shown a surveillance area
100 having
a plurality of sensor systems
120[
1] . . .
120[N] situated
therein. Each of the individual sensor systems
120[
1] . . .
120[N]
monitors a respective sensory area
110[
1] . . .
110[N], each
individual area being defined by sensory perimeter
130[
1] . . .
130
[N], respectively.
With continued reference to FIG. 1, the sensory areas
110[
1] .
. .
110[N] are shown overlapping their respective adjacent sensory areas.
While such an arrangement is not essential to the operation of a surveillance system
or a surveillance system constructed according to the present invention, overlapping
the sensory areas in this manner ensures that the entire surveillance area
100
is sensed by one or more individual sensor systems and that there are no "blind"
areas within the surveillance area
100. Consequently, an object located
anywhere within the surveillance area
100, that is the focus of a surveillance
activity (not specifically shown in the FIG. 1, and hereinafter referred to as
a "target"), may possibly be sensed by one or more of the sensor systems
120[
1]
. . .
120[N].
Advantageously, when multiple sensor systems are arranged in a manner
like that shown in FIG. 1, even if a target moves within the surveillance area
100, it will be sensed by other subsequent sensor systems when that target
is located within their respective sensory area(s). Additionally, when a target
is sensed by multiple sensor systems because it is situated within overlapped sensory
areas of multiple sensor systems the reliability of the sensed data may be improved
as multiple, independent sensor systems provide their independent sensory data.
Importantly, while the FIG. 1 illustrates only a single sensor system
(i.e.,
120[
1]) within a particular sensory area (i.e.,
110[
1]),
it should be understood and appreciated by those skilled in the art that multiple
sensor systems may occupy a single sensory area. Furthermore, the multiple sensor
systems need not even be responsive to the same sensory stimulus. For example,
a given sensory area could have sensor systems responsive to audible, vibrational,
chemical, visual or non-visual stimulus, or a combination thereof. In this manner,
a target that did not produce, for example, an audible signature may nevertheless
produce a vibrational signature, capable of being detected by a vibrational sensor
system. Still further, adjacent or overlapping sensory area(s) may have dissimilar
sensor systems or sets of sensor systems, depending upon the design of the surveillance
area and its sensory components and requirements.
Turning our attention now to FIG. 2, there is shown a surveillance system
according to the present invention. Specifically shown in FIG. 2, surveillance
area
100 includes a plurality of sensor systems
120[
1] . .
.
120 [N], which are shown arranged in a manner consistent with that shown
in FIG. 1.
Each of the sensor systems
120[
1] . . .
120[N] is in communication
with communications hub
210 via individual sensor communications links
230[
1]
. . .
230[N], respectively. It should be noted that for the sake of clarity,
not all of the individual communications links are shown in the FIG. 2. Nevertheless,
it is understood that one or more individual communications link(s) exist from
an individual sensor system to the communications hub
210.
Further, such communications link(s) may be any one or a mix of known types.
In particular, while surveillance systems such as those described herein are particularly
well-suited (or even best suited) to wireless communications link(s), a given surveillance
application may be used in conjunction with wired, or optical communications link(s).
Advantageously, the present invention is compatible with all such links.
Of course, surveillance applications generally require flexibility, distributed
across a wide geography including various terrain(s) and topographies. As such,
wireless methods are preferably used and receive the most benefits from the employment
of the present invention. Of particular importance to these wireless systems, is
the very high transmission compression rates afforded, thereby allowing the maximum
amount of data transmitted in a minimal amount of time. Such benefit(s), as will
become much more apparent to the reader, facilitate scalability as additional wireless
sensor systems may be incrementally added to an existing surveillance area as requirements
dictate, and because sensory systems do not have to transmit for extended periods
of time, power consumption is reduced and detectability (by unfriendly entities)
of the sensor systems themselves is reduced.
The communications hub
210 provides a convenient mechanism by which to
receive data streams transmitted from each of the sensor systems situated within
the surveillance area
100. As can be appreciated by those skilled in the
art, since the surveillance area
100 may include hundreds or more sensor
systems, the communications hub
210 must be capable of receiving data streams
in real time from such a large number of sensor systems. In the situation where
different types of communications links are used between communications hub
210
and individual sensor(s) systems, the hub
210 must accommodate the different
type of communications link or additional hub(s) (not specifically shown) which
do support the different communications link(s) may be used in conjunction with
hub
210.
As a further note, and as will be described in more detail later, the communications
links
230[
1] . . . .
230 [N] are preferably bi-directional
such that configuration/command/control information may be provided to an individual
sensor system from the master processing system
220. Typically, the uplink
(master processing system to sensor system) need be of lower bandwidth than the
downlink, as the volume of data sent in the uplink direction is usually much less.
As depicted in FIG. 2, the master communication link
240 provides a bi-directional
communications path(s) between the master processing system
220 and the
communications hub
210. Data received by the communications hub
210
via communications links
230[
1] . . .
230[N] are communicated
further to the master processing system
220 via the master communications
link
240. Necessarily, the master communications link
240 in the
downlink direction is of sufficient bandwidth to accommodate the aggregate traffic
received by communications hub
210. Similarly, the uplink bandwidth of the
master communications link
240 while typically much less than the downlink
bandwidth must support any uplink communications from the master processing system
220 to the plurality of sensor systems situated in the surveillance area
100.
According to the present invention, master processing system
220
receives data from one or more sensors
120[
1] . . .
120[N]
positioned within the surveillance area
100 and further processes the received
data thereby deriving further informational value. As can be appreciated, the data
contributed from multiple sensor systems with the surveillance area
100
permits the operation of powerful "sparse arrays" of sensor systems, exhibiting
much higher classification/tracking potential than existing systems.
In a preferred embodiment, and according to the present invention, the master
processing system
220 offers equivalent functions of present-day, commercial
computing systems. Consequently, the master processing system
220 exhibits
the ability to be readily re-programmed, thereby facilitating the development of
new data fusion methods/algorithms and/or expert systems to further exploit the
enhanced data fusion potential of the present invention.
Turning now to FIG. 3, there is shown in block diagram form a generic sensor
system constructed according to the present invention. More specifically, the construction
of sensor system
120[
1] . . .
120[N] is like those shown in
our discussion of earlier figures, namely FIGS. 1 and 2. In operation, a sensory
input signal (stimulus)
310 is received by sensor element
320 of
sensor system
120[
1] . . .
120[N] producing a raw target signature
(not specifically shown) which is operated on by analog/digital converter
330,
thereby producing digital representation of raw target signature
335.
It is anticipated that the specific sensor element
320 which is used will
depend upon the particular environment in which the sensor system
120[
1]
. . .
120[N] is deployed and the type/nature of the target being sensed.
In particular, acoustic, seismic, thermometric, barometric, magnetic and photonic
types of direct measurement sensors are all compatible with the inventive teachings
of the present application. In addition, indirect sensors, i.e., certain types
of magnetic, may be used to measure changes or disturbances in magnetic field that
have been created or modified. Such measurements may be later used to derive information
on properties direction, presence, rotation, angle or electrical currents. Finally,
while our discussion so far has been limited to "passive" types of sensing, the
present invention is not so limited. In particular, "active" types of sensing,
i.e., RADAR, may be advantageously used with the present invention as well. In
such situations, active elements (not shown in FIG. 3) may be incorporated to provide
the active sense capability.
Continuing with the discussion of the sensor element
120[
1]
. . .
120[N] depicted in FIG. 3, the digital, raw target signature
335
is generically pre-processed, (i.e., spectral estimation, noise estimation, filtered).
The pre-processed target signature
345 is then operated on by extractor/compressor
350.
Specifically, extractor
360 of extractor/compressor
350
receives the pre-processed target signature
345 and analyzes and "strips"
or otherwise removes non-essential signal components from the pre-processed target
signature
345 that do not aid in the "sensory purpose" of the surveillance
system, i.e., target detection, classification or tracking. By way of example,
and depending upon the type of target, sensory purpose of the surveillance system,
and specific stimulus being sensed, the bandwidth may be reduced, the dynamic range
may be reduced, or other(s) signal characteristics removed. As depicted in the
FIG. 3, the particular extraction(s) performed (shown in the figure as "A B C D
. . . " situated within extractor
360) is/are variable.
Subsequently, compression technique(s) are employed on the extracted
signal
365, thereby reducing the total amount of data necessary to represent
the extracted/compressed signal
375. This compression is performed by compressor
370, which, similarly to the variable extractions provided by the extractor
360, are also variable (shown in the figure as "A B C D . . . " situated
within compressor
370). Advantageously, the particular type of compression
used in a specific situation is dependent upon the extraction type performed by
extractor
360. The process may be iterative, such that an extraction/compression
combination is employed that is optimized for the particular type of sensor element
320.
The optimized, extracted/compressed data signal
375 is transmitted via
transmitter
380 over communication a link
230[
1] . . .
230[N]
downstream to master processing system (FIG. 2
220). Transmitted data received
from a plurality of sensor systems
120[
1] . . .
120[N] are
operated on by master processing system to derive information about the surveillance
area
100 and any target(s) therein.
It is important to note that according to the present invention, each of the
matched
extraction/compression pairs, i.e., A—A, B—B, C—C, D—D,
etc, is preferably optimized for a particular sensor type. As used herein, such
optimization generally means that the extraction is "loss-less", in which significant
features of the sensor specific data are preserved, and the compression scheme
employed provides the optimal compression for that sensor type/extraction. The
result of this inventive notion is that for a particular sensor type, an optimal
compression is employed thereby preserving bandwidth of the transmission facilities used.
By way of example, and to aid the reader in further understanding this matched,
extraction/compression combination, we consider for a moment different types extraction/compression
schemes which could be employed. For example, in MPEG for video, JPEG for still
pictures, and MP-3 for audio, we find highly generic and powerful encoding/compression
solutions which have become industry standards. Accordingly, analogous extraction/compression
pairs (A—A, B—B, etc) are advantageously employed according to the
invention for various sensor(s)/data i.e., acoustic, vibrational, magnetic, etc.,
and become highly flexible and robust solutions for feature analysis, compression,
and transmission for each different sensor type (i.e., acoustic, seismic, magnetic,
etc.) In a specific application to an acoustic distributed sensor system(s), several
candidate "matched pairs" of efficient feature extraction/compression schemes have
been realized which show high compression ratios. Overall compression ratios of
100:1 have been demonstrated and theoretical limits of 300:1 using near lossless
compression are possible, while maintaining essential signal characteristics.
An important aspect of the present invention therefore, is that the sensory stimulus
is efficiently distributed from multiple sensor systems distributed throughout
a surveillance area to a master processor system for subsequent data analysis/fusion.
Contributing to this inventive notion is a family of generic extraction/compression
method pairs which are individually optimized for a particular sensor element type
and their use results in very high overall data compression ratios while being
low power/processing efficient.
At this point, if the present invention were applied to an acoustic surveillance
system, more powerful beamforming techniques (a processing technique in which information
from a number of microphones is combined to increase directionality, noise suppression
and range of sensing) may be employed at the overall surveillance system level
than can be achieved if sensory information were processed "locally" at each sensor
site in a surveillance area. In particular, current schemes that attempt to effect
high performance acoustic surveillance, typically employ expensive sensor arrays
(a number of microphones, spread out over a very-limited geography) and similarly
expensive local processing. In order to accomplish the beamforming, specific processing
techniques must be designed exactly to the specific array design (number and dimensions
of microphones). These multiple-microphone beamforming processing activities are
inherently difficult to implement due to their complexity and power consumption
thereby rendering them largely unavailable to remote, field surveillance areas.
In contrast, and according to the present invention, an exemplary acoustic surveillance
capability does not require specialized or expensive remote field processing systems.
Sensors may be individual microphones, as part of an efficient, low cost, small-sized
unit. Sensor inputs are analyzed, encoded, and efficiently compressed for the transmission
to a powerful master processing system, which then exploits the theoretical limits
of data fusion. Furthermore, the individual sensor systems distributed throughout
the surveillance area, need only transmit data to the master processing system
when they are actually receiving a sensory stimulus. Of course, even when sensor
activity is pronounced—according to the present invention non-essential signal
components are extracted, and the extracted signal is then compressed in a particular
manner such that the extraction/compression is optimized. Consequently, in the
case of this acoustic surveillance example, more powerful beamforming techniques
may be employed at the master processing system.
Additionally, by collecting and analyzing the TOTAL sensor information
available from a surveillance area in a single master processing system, the ENTIRE
surveillance area is constantly being surveilled, and more useful information may
be derived. Overall sensor transmissions to the master processing unit can be reduced
by taking advantage of the fact that the combination of MANY sensors inherently
improves system performance when considering the advantage of a high performance
system level data fusion solution to target classification and tracking. Consequently,
the master unit may employ selective receipt of information from the sensor field,
which could include turning certain sensors on and off or duty cycling.
Yet another characteristic of the invention emerges in the context of the acoustic
beamforming example described above. In particular, the present invention provides
the ability to generate or otherwise create "on the fly" sparse arrays within a
sensor field or surveillance area. Such a feature would be extremely difficult
or impossible with existing data acquisition surveillance methodologies that use
preset algorithms or methods deployed in the field. Stated alternatively, by analyzing
ALL of the data/information received from an entire surveillance area by a master
processor, any combination of sensor systems may be used for sparse array beamforming.
In particular, those sensor systems which are for example, the most efficient at
a particular time/place for a particular target. With such a system, as taught
by the present invention, a sparse array may be "constructed around" a target,
as that target moves throughout the surveillance area.
Still another aspect of the present invention that can be readily appreciated
by those skilled in the art, the use of feature extraction optimally matched with
compression allows a very substantial reduction in the total amount of data transmitted
from a sensor system to the master processing system. Reductions of 100 to 1, or
more, are realizable with the present invention. Consequently, the master processing
system, further facilitating the development and implementation of sophisticated
data fusion methods and techniques receive a smaller volume of data. Of further
advantage, the master processing system may direct specific sensor systems, which
matched pair of extraction/compression techniques, are to be used, in real time,
depending upon for example, the specific target being surveiled.
In addition to maximizing the potential development and application of data fusion
techniques, a system constructed according to the teachings of the present invention
should be highly scalable, as the significant reduction in data transmitted permits
the addition of significant numbers of sensor systems to the surveillance system
without exhausting available system resources. Lastly, the present invention should
lead to further innovative designs of sensor systems, which are capable of supporting
new sensor elements, without requiring hardware/software modification(s).
Turning our attention now to FIG. 4A, there is shown a flow chart depicting
a sensor method according to the present invention. In particular, collective steps
401, are all performed within a sensory system, which is distributed throughout
a surveillance area.
Sensor specific stimulus is received and data collected at step
402.
That collected data is pre-processed at step
404 where it is converted from
an analog sensor domain to a digital domain for further processing and transmission.
The pre-processed, collected data is then treated by extraction/compression matched
pair
403, where non-essential signal information is first extracted (step
406) and then compressed (step
408) by a compression scheme matched
to the extraction scheme. As noted in earlier discussions, the extraction/compression
matched pair
403 is preferably optimally matched to the specific sensor
type employed. This compressed data is then subsequently transmitted at step
410
to a master processor where it is received (along with other data streams from
sensor systems throughout a surveillance area) for analysis/fusion.
Shown further in FIG. 4A, off-chart input
405, may provide specific
direction to the sensory system from the master processor. In this manner, further
refinement to the matched extraction/compression scheme may be provided from the
master processor during a surveillance.
Lastly, turning now to FIG. 4B, there is shown a flow chart depicting the
master processor method that is matched to the sensor system method of FIG. 4A.
In particular, collective steps
420 operate within a master processing system
that first receives at step
422 multiple data streams from a number of sensor
systems included in a surveillance area under interest. The collective data is
analyzed or "fused" with one another at step
424.
Importantly, the data fusion/analysis process may cause some further
direction of the sensor system(s) by the master processor. If, as determined at
step
426, such further direction is required, it is performed at step
428
and out to sensor system(s) at block
405.
If no sensor system direction is required, then the master processing system
continues
with the analysis/fusion processes at step
430, and further continuing with
the receipt of multiple data streams, step
422.
Of course, it will be understood by those skilled in the art that the foregoing
is merely illustrative of the principles of this invention, and that various modifications
can be made by those skilled in the art without departing from the scope and spirit
of the invention. In particular, different sensor(s) and or master processor system
combinations are envisioned. Additionally, alternative extraction/compression schemes
will be developed, in addition to those already known and well understood. Accordingly,
my invention is to be limited only by the scope of the claims attached hereto.
*
