Angle-Doppler Compensation for Multistatic MIMO Radar

A MIMO Multistatic radar system consists of multiple bistatic MIMO pairs working in potentially different configurations. If a bistatic pair in a Multistatic MIMO radar system employs multiple transmit and receive elements, this increases the dimensionality of the data received over a Coherent Processing Interval (CPI), which in turn increases the training data needed to reliably estimate the covariance matrix. This, coupled with the non-stationarity in the received data resulting from the bistatic geometry further degrades the quality of the covariance matrix estimate used in the adaptive detector. In [1], Bell et al. presented a physics based MIMO clutter model, and showed that lack of training data support renders the MIMO radar unfeasible in that the individual bistatic pairs can outperform the overall MIMO system. In addition to that, a radar collects target free training samples from the range cells adjacent to the cell under test, and because of the range-dependent variation in the clutter angle-Doppler behavior, the data used from these target-free range bins causes an estimation error, and degrades the STAP performance. To counter the effects of limited training data, we need to investigate techniques that perform reasonably well in data limited scenarios, and to ensure that the training data does not cause a significant performance degradation due to angleDoppler variation in the clutter associated with range, we need to study techniques to compensate for this range-dependent angleDoppler variation. We show that the physics-based clutter model presented in [1] can be approximated as an AR process of model order 4, and that angle-Doppler compensation can be used to align the spectral centers in the training data obtained from target-free range bins. This has implications for reducing the error associated with estimating the multichannel AR parameters from available training data.