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When Target Motion Matters: Doppler Coverage in Radar Sensor Networks. Presenter: Yin Sun Xiaowen Gong, Junshan Zhang, Douglas Cochran School of Electrical, Computer, and Energy Engineering Arizona State University. INFOCOM 2013, Apr. 17th, 2013. Outline. Introduction
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When Target Motion Matters: Doppler Coverage in Radar Sensor Networks Presenter: Yin Sun Xiaowen Gong, Junshan Zhang, Douglas Cochran School of Electrical, Computer, and Energy Engineering Arizona State University INFOCOM 2013,Apr. 17th, 2013
Outline • Introduction • Doppler Coverage Model • Characterization of Doppler-Covered Regions • Critical Sensor Density for Doppler Coverage under A Deployment Pattern • Conclusion
Passive Sensing vs. Active Sensing • Passive sensors, such as thermal, seismic, optical, infrared sensors, detect natural radiation emitted or reflected by an object of interest (i.e., target) • Most sensor network literature consider passive sensors • Radars are active sensors that actively emit radio waves and collect the echo reflected by the target (e.g. people, vehicles, aircrafts, ships) • Most radar literature focus on single radar systems • Radars have a number of advantages over passive sensors • Typically have larger sensing ranges • Can work under severe conditions (e.g. darkness, haze, rain, snow)
Radar Sensing Model • Range-basedsensing: SNR model • Received target signal power: (SNR contour is circle) • Radar constant K captures physical characteristics (e.g., transmit power, radar cross section) • Angle-basedsensing: Doppler frequency shift (DFS) model • DFS is the frequency difference between the emitted and received radar signals due to the relative velocity between a radar and a moving target Δ
Clutter Spoils Radar Sensing • Clutters are echoes from undesired objects (e.g., rocks, trees, clouds) • Can be much stronger in magnitude than that from a target • The magnitudedepends on physical characteristics of undesired objects (e.g., material, shape) which may not be known • A salient challenge for radar compared to passive sensors • Key observation: Clutter objects are typically stationary or slow-moving compared to the target • DFS can be exploited for detection of moving target
Doppler Processing for Sensing • Moving target indication (MTI): An effective technique for exploiting the DFS • 1. Apply high-pass filter in the DFS domain to suppress clutter • 2. Perform SNR-based detection (e.g. energy detection) in the filtered signal • Simple to implement with low computational cost • The filtered signal contains the target signal if and only if Δis large enough (Δ) clutter moving target moving target noise DFS cutoff frequency high-pass filter DFS
Networked Radars • Radar network is a promising paradigm for sensor network applications • Networked radars offer diversity in both range (SNR) and angle (DFS) for potential better sensing capability • Modern radar is becoming more affordable and more efficient, possible for larger-scale networked deployment • Little attention has been paid to radar networks, especially coverage problems no target target detected! no target • A coverage model is lacking for radar networks that exploit the DFS • Existing coverage model based on range (SNR) only: A point is covered by a sensor if and only if is in the sensing range of (i.e., ) • DFS has been studied mostly for single radar systems but NOT for coverage of radar networks
Doppler Coverage Model • We propose Doppler coverage model based on bothrange and angle • If a target is Doppler-covered (D-covered), then there exists some radar that can observe both high SNR and large DFS • Effective Doppler angle is determined by the cutoff frequency • New challenges: 1) The D-coverage depends on both distances and angular positions of radars from target 2) A radar can contribute two types of D-coverage: up-Doppler and down-Doppler E.g.: is not D-covered is down-D-covered DEFINITION: A target at a point moving in direction is Doppler-covered by a radar if and only if and or ; A point is Doppler-covered if and only if any direction from is Doppler-covered by some radar.
Coverage List • Question 1: How to find all the Doppler-covered points (regions) for arbitrarily deployed sensors? • How to check if a point is D-covered? Coverage list for a point • 1. Construct an image point for each in the set of sensors that cover (“cover” in the range sense, i.e., ) such that • 2. Order all the points and based on their angular positions with respect to E.g.: , (or for short) LEMMA 1: A point is Doppler-covered by if and only if for any pair of neighbor points and in constructed from .
Safe/Complementary Safe Regions • How to check the condition in Lemma 1 for all points? Safe and complementary safe regions for a pair of radars • Safe region: outside the circumscribed circles of where • Complementary safe (c-safe) region: inside the circumscribed circles ofwhere LEMMA 2: for any in the safe region of and ; for any in the complementary safe region of and .
Sub-Region Partition • How to find a sub-region in which all points have the same coverage list? Sub-region partition • Two points covered by the same set of sensors may have different coverage list E.g.: LEMMA 3: For a region covered by , is partitioned by all the lines each passing through a pair of sensors in into a set of sub-regions such that all the points in a sub-region have the same coverage list constructed from .
Doppler-Covered Regions • Answer 1: We develop an efficient method for characterizing Doppler-covered regions • 1: Partition the entire region into sub-regions such that all points in a sub-region have the same coverage list • 2: For each sub-region, construct safe or c-safe region for each pair of neighbor points in its coverage list (construct safe region if both are non-image points or both are image points; otherwise, construct c-safe region) , , The shaded regions are D-covered by }
Critical Sensor Density • Question 2: What is the critical sensor density (minimum number of sensors) under a particular deployment patternsuch that the entire region is Doppler-covered? • A natural question when we can control the deployment locations • Ignore boundary effect and focus on asymptotic case (typical in sensor coverage literature) • Optimal deployment pattern is difficult to find even for passive sensor networks • We consider a deployment pattern consisting of polygons (e.g., triangles, rectangles, hexagons) • There exists a unit region such that is D-covered if and only if the entire region is D-covered
Critical Sensing Range • Critical pattern size : maximumpattern sizegiven and such that the unit region is D-covered • pattern size : a parameter characterizing the sensor density of a deployment pattern (e.g., side length of a regular triangle for regular triangle pattern) • is increasing in and increasing in • Critical sensing range : minimumsensing range given and such that the unit region is D-covered • is decreasingin and increasing in • Critical sensor density critical pattern size critical sensing range • If we find the closed-form of as a function of parameterized by , • then is the inverse function of • Answer 2: We design CSR Algorithm (find Critical Sensing Range): input output
Numerical Results • Doppler-covered percentage: percentage of D-covered areas • An entire region of 100 X 100 under uniformly random deployment of sensors • Averaged results of 100 runs • Sensing range (a) (b) We observe that 1) Performance is better for a larger 2) A larger sensing range significantly improves performance
Conclusion • Contribution • Introduced a novel Doppler coverage model to study the coverage of radar networks that exploit both SNR and DFS for moving target detection • Developed an efficient method for characterizing the Doppler-covered regions for arbitrarily deployed sensors • Can be used to evaluate the coverage of any deployed radar networks that exploit DFS for moving target detection • Designed CSR Algorithm for finding the critical sensor density for Doppler coverage under a polygon deployment pattern • Can be used to estimate the number of radars needed for Doppler coverage • Future Work • Extending the coverage model: Barrier coverage, k-degree coverage … • Extending the Doppler model: Information of target’s motion … • Bistatic/multistaticradar networks
Thank You ! Questions ? Please send any questions to the co-authors at xgong9@asu.edu; junshan.zhang@asu.edu
Range-based Detection: SNR Model • Monostatic radar: co-located radar transmitter and receiver • Received target signal power : (SNR contour is circle) • K: depends on physical layer characteristics, e.g., transmit power, antenna gains, radar cross section radar Tx and Rx • Bistatic radar: separated radar transmitter and receiver • Received target signal power : radar Tx radar Rx
CSR Algorithm • CSR Algorithm (find Critical Sensing Range): input output • Phase 1: coarse-grained search : lower bound of : upper bound of : set of sensors that must cover all points in when : set of sensors that must or possibly cover some points in when : set of sensors that must not cover any points in when • Phase 2: divide and conquer approach Split a coverage list into partial coverage lists , , , ,, Sub-routinePCSR Algorithm : PCSR[, ] finds the minimum sensing rangerequired to Doppler-cover all the directions (if any) from any point and between and that can not be Doppler-covered by or
CSR Algorithm: Case Study • CSR Algorithm applied for regular triangle pattern • (a) (unit region) can be Doppler-covered by • (b) can be Doppler-covered by but not by ) )