Multi-Sensor Measurements for the Detection of Buried Targets Waymond R. Scott, Jr. and James McClellan School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta, GA 30332-0250 [email protected]404-894-3048 MURI Review 8-3-05 Scott/McClellan, Georgia Tech 2 Outline Introduction Three Sensor Experiment Multi-static Radar Seismic Array Accomplishments/Plans
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Multi-Sensor Measurements for the Detection of Buried Targets
Waymond R. Scott, Jr. and James McClellanSchool of Electrical and Computer Engineering
Georgia Institute of TechnologyAtlanta, GA 30332-0250
Experimental Scenario #16 Mines> 20 Clutter objectsRelatively uniform distribution
Experimental Scenario #27 Mines> 25 Clutter objectsNon-uniform distribution
Experimental Scenario #3Non-uniform distribution of 7 Mines (2 AT, 5 AP) and 57 clutter objectsRock field surrounding AP mine and canAP mines and clutter objects grouped around and on top of AT mines
VNA has one source and two samplers (A & B)T1 P1 T2 P2R1R2R3R4
VNA & switch operationResponse from 8 bistatic apertures are obtained by the following procedure:
1. Initialize all switches2. Obtain bistatic responses from T1-R1 and T1-R33. Throw internal switch4. Obtain bistatic responses from T2-R1 and T2-R35. Throw internal switch and external switches6. Obtain bistatic responses from T1-R2 and T1-R47. Throw internal switch8. Obtain bistatic responses from T2-R2 and T2-R4
VNA sweeps 401 frequencies from 60MHz to 8.06GHz (20MHz increment)Control computer stores the raw responses in the frequency domainThe raw responses are calibrated after the measurement
Calibration
Free space response (FREE)Free space is simulated by pointing the array toward absorber-padded cornerSubtraction removes direct coupling in the system
Through response (THRU)Antenna ports are connected by a 5ft cableDivision removes distortion in the cables feeding the antenna
The array is scanned over 1.8m x 1.8m scan regionThe scan region is gridded into 91 x 91 points (∆x = ∆y = 2cm)
Per pointGPR obtains 8 bistatic responses at 401 frequency pointsInternal switch throw: 4 timesExternal switch throw: twiceTime: approximately 6 seconds
Per experimentData size: 8 (pairs) x 91 x 91 (points) x 401 (freq) x 8 (complex single) = 208 MBInternal switch throw: 33 124 timesExternal switch throw: 16 562 timesTime: approximately 14 hours
Targets are buried 1cm – 13cm deep when measured from the surface of the sand to the top of the targetAntennas are elevated by 10cm from the sandIn cluttered-surface experiment:
Rocks are scattered over the scan regionRock density is empirically chosen to maximize the clutter effect
Sand with Clean Surface Sand with Cluttered Surface
Anti-tank mines: VS-1.6, VS-2.2, and TMA-5Anti-personnel mines: TS-50, PFM-1, M-14, and mine simulant Clutter objects: metal sphere, rock, crushed can, and nylon cylinder
Allowing contact with the ground makes is possible to construct robust and low-cost sensors arrays
Developed such a sensor using COTS componentsSensor weight (6 oz.) is much less than typical landmine detonation weights (more than 10 lbs. for AP landmines, much greater for ATlandmines)Array for this work
3 lines of 10 sensors1.35 inches between sensors in each line (fixed by sensor configuration)Variable spacing between lines
• Currently 4 inches (10 cm)• Maximum of 11 inches (29 cm)
Experiment shown with VS-1.6 AT Landmine Buried 5cm Deep
AccomplishmentsDeveloped three sensor experiment to study multimodal processing
Developed new metal detector and a radarInvestigated three burial scenariosShowed responses for all the sensors over a variety of targetsDemonstrated possible feature for multimodal/cooperative processingDeveloped new 3D quadtree strategy for GPR data
Developed seismic experiments, models, and processing Developed optimal maneuver algorithm to locate targets with a seismic array Demonstrated reverse-time focusing and corresponding enhancement of mine signatureDemonstrated imaging on numerical and experimental data from a clean and a cluttered environmentModified time-reverse imaging algorithms to include near field DOA and range estimates. The algorithms are verified for both numerical and experimental data with and without clutter.Modified wideband RELAX and CLEAN algorithms for the case of passive buried targets. The algorithms are verified for both numerical and experimental data with and without clutter. Developed a vector signal modeling algorithm based on IQML (Iterative Quadratic maximum Likelihood) to estimate the two-dimensional ω-k spectrum for multi-channel seismic data.
Developed multi-static radarDemonstrated radar operation with and without clutter objects for four scenariosInvestigated pre-stack migration imaging of multi-static data
Buried structuresDeveloped numerical model for a buried structureDemonstrated two possible configurations for a sensorMade measurement using multi-static radar
Incorporate reverse-time focusing and imagingIncorporate multi-static radarMore burial scenarios based on inputs from the signal processorsLook for more connections between the sensor responses that can be exploited for multimodal/cooperative imaging/inversion/detection algorithms
Imaging/inversion/detection algorithmsUse reverse-time ideas to characterize the inhomogeneity of the groundInvestigate the time reverse imaging algorithm for multi-static GPR data.Investigate the CLEAN and RELAX algorithms for target imaging from reflected data in the presence of forward waves with limited number of receivers.Develop elimination and end-game strategies for seismic detection with a maneuvering arrayInvestigate joint imaging algorithms for GPR and seismic data.