Abstract
In the presence of arbitrary array errors and angle mismatch, performance on target detection and angle estimation will be degraded due to steering vector mismatch. Thus, a robust target detection and estimation algorithm for airborne STAP radar is developed. First, utilizing the spatial-temporal coupling property of the ground clutter, array steering vectors are well estimated by fine Doppler localization of the mainlobe clutter. Then, the robust subspace detector spanned by these estimated array steering vectors is developed, which can improve the detection performance for the targets not located in the look direction. Finally, target angle estimation using subspace coefficients, which implements the ML estimator in a reduced-dimensional version, is presented to reduce the computational complexity of the ML estimator. Numerical examples are given to demonstrate the effectiveness of the presented algorithm.
Highlights
The ground clutter seen by an airborne radar is extended in both range and angle
Classical data selection methods include the generalized inner product (GIP) statistic, a combination of the six methods including fast maximum likelihood algorithm (FML), reiterative censoring, adaptive power residue (APR) metric, concurrent block processing, two weight method, and adaptive coherence estimate (FRACTRA)[24], which are widely used in space-time adaptive processing (STAP), can be used here
The objective of this paper is to propose and evaluate the robust target detection and estimation method based on steering vector estimation and the subspace detector against steering vector mismatch resulted from array errors and target uncertainty
Summary
The ground clutter seen by an airborne radar is extended in both range and angle. It is spread over a region in Doppler because of the platform motion. To reduce performance degradation induced by steering vector mismatch, either array calibration or robust beamforming for airborne STAP radar is required. In order to reduce the complexity, the STAP processor generally uses single spatial beam to cover the mainbeam In this case, target angle mismatch often happened. A robust target detection and estimation algorithm for airborne STAP radar is developed against steering vector mismatch. Utilizing the spatial-temporal coupling property of the ground clutter, array steering vectors in the mainbeam are first estimated by fine Doppler localization. To overcome the problem of target angle mismatch with the look direction, the subspace detector spanned by the mainlobe low-rank subspace derived from the estimated steering vectors is developed. (1) Steering vector estimation for arbitrary array error is developed, which is based on the spatial-temporal coupling property of airborne radar clutter.
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