A SAR-Based Algorithm for Imaging of Landmines with GPR

In this paper we propose a new algorithm for enhancement of imaging of plastic cased antipersonnel landmines using a video-impulse GPR. The algorithm is implemented as a non-linear waveform based signal processor integrated with a SAR focusing procedure. The algorithm constructs a SAR-like image of the subsurface using the outputs of the signal processor. The signal processor searches for presence of reference waveform in raw 1D GPR echo-returns and compresses in time all responses similar to it. Simultaneously, the responses with different waveforms, which presumably correspond to clutter, are suppressed. The shape of the predefined reference waveform depends on the angle at which the imaged point is illuminated. This algorithm is integrated into an automated data processing and mine detection scheme generating a detection list. The reference waveform and other algorithm parameters are determined from training datasets acquired in a controlled environment. The performance of the new algorithm is compared against the performance of the sequence of the signal processor without angle dependency and SAR and against a scheme involving a cross-correlation of the input with the same reference wavelet. The improvement achieved by the suggested algorithm is demonstrated in terms of ROC curves. wavelet is a representation of the target response to the excitation by the probing pulse of the radar and is derived from a set of data acquired in controlled environment conditions. The algorithm is implemented as a two-stage signal processor with a raw A-Scan as an input. The local similarity between the input and the reference wavelet is calculated at the first stage of the processor for each time sample, and the penalty functional is applied to it at the second stage. The output signal of the processor is a range profile, in which position of a target response is marked by a very sharp monopulse, while most of the other reflections are suppressed to nearly zero level. A SAR focusing procedure is applied to the output of the signal processor resulting in subsurface images where the presence of the APM was marked more clearly while some very strong sources of clutter, like pieces of shrapnel or barbed wire were suppressed. However, it has been shown that the target's response wavelet changes with the change of the angle at which it has been illuminated. Due to this, any particular target is marked with highest possible amplitude responses in the output of the PLSM algorithm only for the A-Scans, which correspond to a small range of illumination angles. This shortcoming may diminish the performance of SAR focusing and the following detection. The angle dependency of the reference wavelet can be established either by modeling or from a training dataset but it cannot be readily applied due to an angle ambiguity existing in a time-space C-Scans. More precisely, the illumination angle cannot be tracked in the 3-D domain. That is a wavelet appearing at each time sample of an A-Scan taken from such a domain may correspond to any equidistant object and thus come from any illumination angle. In the present paper we resolve this ambiguity by superimposing the PLSM algorithm with the SAR migration technique. In SAR-focused image of an domain for each imaged point there is only one object placed in it, which is considered as a possible source for the wavelet. Therefore the angle ambiguity is resolved and it is possible to image the given point integrating over the accordingly delayed outputs of PLSM algorithm with reference wavelets dependent on the illumination angle.