Moving Multi-Polarization Multi-Transmitter/Receiver Ground Penetrating Radar System and Signal Processing for Buried Target Detection

• US 20160061948A1
• Filed: 06/06/2013
• Published: 03/03/2016
• Est. Priority Date: 06/06/2013
• Status: Active Grant

• Current Assignee: United States Of America As Represented By The Secretary Of The Army (Government of the United States of America)
• Original Assignee: United States Of America As Represented By The Secretary Of The Army (Government of the United States of America)
• Inventors: Ton, Tuan T., Wong, David C., Soumekh, Mehrdad
• Granted Patent: US 9,395,437 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01S 13/0209 Systems with very large relative bandwidth, i.e. larger than 10 %, e.g. baseband, pulse, carrier-free, ultrawideband
• CPC Class Codes: G01S 13/86 Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
• CPC Class Codes: G01S 13/867 Combination of radar systems with cameras
• CPC Class Codes: G01S 13/885 for ground probing prospecting or detecting using electromagnetic waves G01V3/12
• CPC Class Codes: G01S 13/90 using synthetic aperture techniques , e.g. synthetic aperture radar [SAR] techniques
• CPC Class Codes: G01S 7/024 using polarisation effects in waveguides H01P1/165; for aerials H01Q, e.g. H01Q15/22, H01Q15/24, H01Q19/195
• CPC Class Codes: G01S 7/4004 of parts of a radar system

Abstract

A moving ground penetrating radar is comprised of multiple transmitters and receivers with multiple, e.g., Horizontal and Vertical, polarizations to detect buried targets with standoff capability. Novel signal and imaging techniques are used to form high quality radar imagery with low artifacts that are due to various sources of self-induced resonances, e.g., transmitter-receiver coupling, calibration errors, and motion errors in the multi transmitter/receiver channels of the radar system. The irradiated target area image is formed via exploiting both the spatial diversity of the physical multi-transmitter and multi-receiver array and synthetic aperture/array that is generated by the motion of the platform that carries the radar system. The images that are formed from the multiple polarizations are combined to remove surface targets/clutter and, thus, enhance signatures of buried targets.

Claims

1. A method of standoff detection for surface and buried targets in or on the road side of a ground vehicle using RF impulse signal, the method comprising the steps of:

transmitting a sequence of RF impulse signals by using at least one impulse generator paired with a respective transmit antenna while the vehicle moves forward on the road, said transmit antenna being placed at the center of an antenna frame in either horizontal or vertical polarization, the antenna frame being mounted on an articulable telescope boom of the vehicle to enable the radar to be configured for different scanning modes;

receiving the return of impulse RF signals using an array of Vivaldi notch antennas, each regularly disposed as either horizontal or vertical polarization with respect to the antenna frame;

converting the impulse signals received from the Vivaldi notch antennas in analog format to digital format using a digitizer to digitize the analog signal as radar data;

interleaving the converted radar data with header and trailer to incorporate GPS information with the radar data; and

processing the stream of radar data along with the GPS information to produce radar images for storage in computer memory.

2. The method of standoff detection according to claim 1, wherein the sequence of RF transmitted impulse signals are 1 ns wide, 50 volt peak-to-peak RF impulse signals.

3. The method of standoff detection according to claim 1, wherein the different scanning modes are a forward-looking mode optimized for in-road targets detection, a side-looking mode optimized for off-road targets, and a squint-looking mode for both types of targets.

4. The method of standoff detection according to claim 1, wherein said digitizer uses an equivalent time sampling technique to digitize the analog signals at an equivalent rate of 8 G samples/second.

5. The method of standoff detection according to claim 1, wherein said header and trailer contain geo-locations and time information from a GPS re-sync module.

6. The method of standoff detection according to claim 1, wherein the radar data stream along with the GPS information are archived and/or processed to produce said radar images for storage in computer memory.

7. A method to fuse the radar data with image data of a 3-CCD-camera and/or an IR camera to improve the overall detection performance of a standoff detection according to claim 1, the method comprising the steps of:

using computers to continuously trigger the cameras, transferring captured images to computers, and assigning a frame number to each of the captured images;

using a GPS resync module to store into the computer the GPS times, locations, and the frame numbers of the photo images whenever the cameras are triggered;

after radar images are formed, if suspicious threat is detected in the radar image, then convert radar images from a 2-dimensional into a 3-dimensional perspective as in the camera photo images;

using the GPS data as index to retrieve the corresponding photo images of 3-CCD camera and IR cameras from computer memory; and

fusing camera photo images with radar images to help determine whether a detected threat is sufficiently real.

8. A method to achieve optimum signal returns for surface and buried targets based on the method of standoff detection according to claim 1, comprising the steps of:

placing the transmit antennas in either horizontal or vertical polarization for transmitting impulse RF signal;

using two different sets of Vivaldi antennas for receiving the returned impulse RF signals, the first set of Vivaldi antennas, which has the frequency range from 200 MHz to 3000 MHz, is oriented in the vertical polarization, the second set of Vivaldi antennas, which has frequency range from 500 MHz to 3000 MHz, is oriented in the horizontal polarization;

interleaving the location of the receive Vivaldi antennas, wherein the first antenna in the array is from the first set, and the second antenna is from the second set, and wherein the pattern of configuration is repeated for the rest of the receiving antennas in the antenna array; and

collecting antenna data output for image processing, wherein the transmit and two types of receive antennas are spatially-diversified, some of which have H polarization and others with V polarization.

9. A signal processing module for calibration of multi-transmitter/receiver channel images of the method of standoff detection according to claim 1, comprising:

a system model for uncalibrated reconstructed images in a multi-transmitter and multi-receiver radar on a moving platform, wherein

ƒ

_lM(x_m,y_n)=ƒ

_l(x_m−

x_ls,y_n−

y_ls)exp(jφ

_l); and

an iterative correlation-based phase and time-delay estimation algorithm to calibrate multi-transmitter/receiver images using a reference image that is generated from the mean value of the multi-transmitter/receiver images in each iteration.

10. A signal processing module for image enhancement via t-score weighting that generates an enhanced full-resolution image from multi-transmitter/receiver images of the method of standoff detection according to claim 1, wherein the module uses the ratio of their mean image and their standard deviation or t-score image.

11. A signal processing module of the method to achieve optimum signal returns for surface and buried targets according to claim 8 to fuse coherent complex four images that are formed from four polarizations, that is, VV, VH, HV and HH, via an adaptive filtering method to suppress the surface targets/clutter while enhancing the signatures of buried targets, comprising:

a continuous-domain multidimensional signal model and its discrete version to relate multi-polarization;

a localized adaptive filtering method based on LSSP to calibrate two images at different polarizations;

a forward and backward LSSP approach to create a difference image or SSD image, that represents changes or buried targets in the two images at different polarizations; and

a spatially-varying version of LSSP, global signal subspace processing, to calibrate two images at different polarizations using a 2D spatially-varying filter that produces an SSD image that does contain boundary artifacts between the subpatches that are used in LSSP.

12. The signal processing module according to claim 11, wherein said continuous-domain multidimensional signal model and its discrete version to relate multi-polarization via a two-dimensional linear spatially-varying are for VV and VH images based on:

ƒ

_VH(x,y)=∫

ƒ

_VV(x−

u,y−

v)h_xy(u,v)dudv.

13. The signal processing module according to claim 11, comprising:

simultaneously transmitting two different and uncorrelated pulses or waveforms using radar transmitters with different polarizations; and

matched filtering to separate the resultant echoes that are generated via illumination of the target area with the two uncorrelated transmissions at the Horizontal and Vertical polarizations.

14. The signal processing module according to claim 13, wherein said two different and uncorrelated pulses or waveforms have horizontal and vertical polarizations based on:

∫

P_H(t)p*_V(t−

τ

)dt=0.

15. The signal processing module according to claim 13, wherein said pulses are uncorrelated in time such that their cross-correlation is zero for all relative time delays of the two pulses.

16. A signal processing system for self-adaptive calibration of measured echoed data using self-induced resonance SIR signals, comprising:

generating uncalibrated measured data based on a system model of a single transmitting radar and a single receiving radar on a moving platform that are contaminated with self-induced resonance SIR signals, wherein

s_lM(t,u_j)=┘

s_l(t,u_j)+s_lSIR(t)┘

*h_l(t,u_j); and

applying a correlation-based time-delay and transfer function estimation algorithm to calibrate the measured radar data using a reference SIR signal that is generated via averaging the measured data in an aperture domain for self-adaptive calibration of measured echoed data using self-induced resonance SIR signals.

17. The signal processing system according to claim 16, wherein an adaptive filtering algorithm is used to suppress the SIR signals in the measured radar data using a reference SIR signal that is generated via averaging the measured data in the aperture domain.