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Airborne radar systems employing radar sensor arrays utilize multi-channel (MC) signal processing techniques for optimal detection and localization of targets. The detection and localization statistics have mathematical structures that typically require evaluating the inverse of an estimated covariance matrix. Due to the size of sensor arrays and the number of pulses in a coherent processing interval...
We continue our investigation into the new class of two-dimensional autoregressive relaxed models (ldquorelaxationsrdquo) for space-time adaptive processing (STAP) applications. Previously reported results on the DARPA KASSPER simulated dataset for airborne side-looking radar are now complemented by STAP performance analysis for all range bins and varying antenna-array errors. We discuss the variability...
We analyze the performance of a recently described class of two-dimensional autoregressive parametric models for space-time adaptive processing (STAP) in airborne radars on the DARPA side-looking radar model known as KASSPER Dataset 1. We investigate the trade-offs between signal-to-interference-plus-noise ratio (SINR) degradation (with respect to the optimal clairvoyant receiver) due to the mismatch...
The optimal (adaptive) linear combiner (beamformer) weights for a sensor array are expressed in terms of the inverse of the multi-channel (MC) covariance matrix. Also, minimum variance (Capon) spectral estimators of the sensor array also depend on the same inverse. Rather than form an estimate of the covariance matrix directly from the available data and inverting it, an alternative direct estimate...
Airborne radar systems employing radar sensor arrays utilize multi-channel (MC) signal processing techniques for optimal detection and localization of targets. The detection and localization statistics have mathematical structures that typically require the inverse of an estimated covariance matrix in order to be evaluated. Due to the size of sensor arrays and the number of pulses in a coherent processing...
In side-looking ground moving target indication (GMTI) radar, the 2-dimensional (2D) space time (azimuth-Doppler) domain can adequately define a clutter spectrum which is accurate for all range gates. However, in applications where the array boresight is not perpendicular to the velocity vector (e.g. forward-looking radar), the azimuth-Doppler clutter spectrum exhibits a dependence on elevation angle-of-arrival,...
In a seminal paper, two algorithmic versions of the multichannel parametric adaptive matched filter (PAMF) applied to space-time adaptive processing (STAP) in an airborne radar application were shown to achieve superior test detection statistics over the conventional adaptive matched filter (AMF), which uses a non-parametric approach to estimate the detection weight vector. In fact, the performance...
Close-in sensing is needed for urban warfare operations, where ground moving target indication (GMTI) could be provided via forward or rear-facing multi-function array radars mounted on small highly-maneuverable airborne platforms. However, airborne radar arrays oriented any direction other than side-looking cause an elevation dependent angle-Doppler relationship in the clutter returns. This non-stationarity...
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