This tutorial provides a brief overview of space-time adaptive processing (STAP) for radar applications We discuss space-time signal diversity and various forms of the adaptive processor, including reduced-dimension and reduced-rank STAP approaches Additionally, we describe the space-time properties of ground clutter and noise-jamming, as well as essential STAP performance metrics We conclude this tutorial with an overview of some current STAP topics: space-based radar, bistatic STAP, knowledge-aided STAP, multi-channel synthetic aperture radar and non-sidelooking array configurations

A STAP overview

This paper describes the impact of clutter nonstationarity on space-time adaptive processing (STAP) performance in a sparse aperture, spaceborne, moving target indication radar scenario and then presents mitigating techniques. Clutter nonstationarity introduces large estimation losses when applying traditional STAP techniques, since STAP requires knowledge of clutter statistics for effective cancellation. Results have previously been shown indicating significant improvements achieved by using reduced-dimension STAP techniques minimizing nonstationarity via localized training; in one instance, the estimation loss was reduced from an average of about 14 dB using joint domain optimum (JDO) STAP to about 6.5 dB using the extended factored algorithm (EFA). This work introduces a steering vector correction method and also applies the extended sample matrix inversion (ESMI) technique to further mitigate clutter nonstationarity. Both of these methods produce good results, with steering vector correction outperforming ESMI in the scenarios tested. Using the combination of EFA and steering vector correction, the average estimation loss was reduced from about 14 dB to 4 dB for the scenario mentioned above, similar to the 3 dE3 loss expected in stationary clutter environments with the same amount of data used to compute the covariance estimate. TABLE OF CONTENTS ........................................................................

http://ieeexplore.ieee.org/iel5/8735/27670/01235127.pdf

Adaptive processing in a nonstationary spaceborne environment

Sparse arrays provide potential for improving the minimum detectable velocity (over 3 m/s improvement for sidelooking radar) of spaceborne moving target indication radar for a given physical aperture. This paper examines the benefits and some of the challenges resulting from employing sparse arrays: grating lobes introduce ambiguities that may create Doppler blind zones; area coverage rate may reduce due to a narrower antenna main beam for coherent transmission; and intrinsic clutter motion may reduce the usable fraction of the Doppler space. We consider the application of orthogonal transmit waveforms to increase area coverage rate, as well as frequency diversity and aperiodic subarray spacings to mitigate Doppler blind zones.

Configuring a sparse aperture antenna for spaceborne MTI radar

This paper describes signal-processing aspects associated with a distributed aperture spaceborne sensor (DASS). DASS offers a number of advantages over a monolithic system. The cost is a more complex signal processing architecture. This paper describes the SINR losses associated with both a single waveform transmitted simultaneously from all satellites and the SINR losses associated with transmitting orthogonal waveforms from each of the satellites. The losses associated with the presence of real-world effects, such as phase errors, are included for both cases. Simulation results are given describing the loss characteristics of a DASS. It is shown herein that a two-dimensiona l DASS using joint domain optimum space-time adaptive processing (STAP) suffers high estimation losses due to a strong antenna taper in elevation. We demonstrate that reduced rank STAP methods substantially reduce this loss.

Adaptive signal processing for a spaceborne distributed aperture

Doppler Ambiguity Resolving in Distributed Micosatellites Radar Imaging

This paper investigates the performance of a spaceborne, distributed aperture system operating in a moving target indication (MTI) mode. A cluster of microsatellites, orbiting in proximity, house the antenna subapertures of the distributed array; the subapertures electronically share the transmit function and receive data. We discuss the modeling and simulation of the distributed aperture MTI sensor operation, examine system performance for several scenarios of interest, and discuss specialized signal processing techniques. Our results indicate that among its various attributes, a distributed aperture, spaceborne MTI system provides excellent detection performance potential; sparse aperture signal processing, coupled with space-time adaptive processing, represents a critical, enabling component. Using a spiral spoke cluster and optimal space-time processing, the average SINR loss with respect to the noise-limited case averages about -2 dB for a radial velocity greater than 3 m/s for the analyzed orientation of the cluster.

Daniel A. Leatherwood

Papers

High-fidelity MTI modeling and analysis of a distributed aperture spaceborne concept

Adaptive signal processing for a spaceborne distributed aperture