Laurent Savy

Bayesian sparse estimation of migrating targets for wideband radar

Wideband radar systems are highly resolved in range, which is a desirable feature for mitigating clutter. However, due to a smaller range resolution cell, moving targets are prone to migrate along the range during the coherent processing interval (CPI). This range walk, if ignored, can lead to huge performance degradation in detection. Even if compensated, conventional processing may lead to high sidelobes preventing from a proper detection in case of a multitarget scenario. Turning to a compressed sensing framework, we present a Bayesian algorithm that gives a sparse representation of migrating targets in case of a wideband waveform. Particularly, it is shown that the target signature is the sub-Nyquist version of a virtually well-sampled two-dimensional (2D)-cisoid. A sparse-promoting prior allows then this cisoid to be reconstructed and represented by a single peak without sidelobes. Performance of the proposed algorithm is finally assessed by numerical simulations on synthetic and semiexperimental data. Results obtained are very encouraging and show that a nonambiguous detection mode may be obtained with a single pulse repetition frequency (PRF).

Fast coherent integration for migrating targets with velocity ambiguity

In wideband radar, fast moving targets migrate through range gate during the coherent processing interval. To preserve coherent integration gain, range gate walk has to be taken into account. In this paper, we propose a fast algorithm based on a Keystone-like transform that allows one to perform such an integration in case of velocity ambiguous radar.

Sparse representation of migrating targets in low PRF wideband radar

In wideband (high range resolution) radar, moving targets migrate along the range during the coherent processing interval (CPI). In this paper, we propose to use the information brought by this migration to alleviate the velocity ambiguity that occurs in low pulse repetition frequency (PRF) mode. More specifically, a Bayesian algorithm is implemented to give a sparse representation of the received signal while unfolding properly the range-velocity map. Though computationally intensive, the algorithm demonstrates the possibility of designing a non-ambiguous radar mode with a single PRF in case of a multi-target scenario.

A Migrating Target Indicator for wideband radar

The standard way to suppress clutter in narrowband radar is to use Moving Target Indicator (MTI) cancellation techniques. High Range Resolution (HRR) radars are becoming more and more important because they can detect and track targets more accurately. As for such radars the bandwidth is increased, the resolution is decreased and leads to target range migration over the coherent pulse interval (CPI). Due to this range walk, standard low resolution MTI processing is not adapted anymore to HRR MTI radar data. We propose here to extend the principle of the MTI processing to the wideband case. We refer to this method as the Migrating Target Indicator (MiTI), since it eliminates the non-migrating targets from the received signals.

Clutter calibration for space-time airborne MTI radars

For slow target detection with airborne array radar, the ground clutter Doppler spreading due to the platform movement is a limiting factor, especially for long wavelength radar. It is shown that two procedures for slow target detection (Doppler-angle imaging or space-time processing, and movement compensation) are equivalent, and that an original real-time procedure for antenna array calibration using clutter returns can be combined with these detection techniques to increase subclutter visibility in the presence of high clutter returns.