Abstract
Traditional space-time adaptive processing (STAP) is a strategy for clutter suppression in airborne radar, which requires a large number of computational complexity and secondary data. In order to address the problem, reduced-dimension (RD) STAP is generally used. We propose a novel RD STAP through searching the best channels as the auxiliary channels to cancel the interference. Based on the estimation of the clutter Fourier basis vectors offline, a parameter named angle-Doppler correlation coefficient (ADC 2) is constructed to evaluate the capability of each auxiliary channel in clutter suppression, and the best sets of RD channels can be selected. The proposed algorithm can achieve the best detection performance with the fixed number of auxiliary channel. When the degrees of freedom (DOF) are restricted to a small value, only one auxiliary channel is needed to guarantee the SINR loss less than 3 dB. Therefore, the requirement of the training sample can be reduced, which makes the proposed approach more suitable for the heterogeneous clutter environments.
Highlights
Space-time adaptive processing (STAP) plays an important role in the areas of airborne radar and sonar systems, which collect signals linearly from an array to detect weak targets within severe clutter and jamming environments [1, 2]
It has been long known that increasing the number of degrees of freedom (DOF) enables excellent detection performance, but since the computational complexity and the number of samples for estimation covariance matrix (CCM) are limited, it is difficult to be implemented in practical work [3]
In the case that the DOF is low, that is, only few auxiliary channels are selected, the output signal-to-interferenceplus-noise ratio (SINR) of the proposed approach is less than 3 dB, while the other approaches cannot achieve the same performance and result in poorer clutter suppression
Summary
Space-time adaptive processing (STAP) plays an important role in the areas of airborne radar and sonar systems, which collect signals linearly from an array to detect weak targets within severe clutter and jamming environments [1, 2]. The dimensionality reduction and rank reduction techniques are explored extensively and addressed in the literature When it comes to reduced-dimension (RD) STAP, some typical suboptimal approaches like the factor approach [7], the joint domain localized (JDL) [8], and the space-time multiple-beam (STMB) [9] have been proposed, which employ a fixed dimension reducing transformation prior to the processing. A multistage multiple-beam (MSMB) technique is proposed in [11, 12], based on the principle of selecting auxiliary channels to cancel the interference components in the main channel clearly It is not appropriate for engineering applications because a large amount of calculation is needed.
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