Adaptive beamformers at the element level usually require a great number of training samples and the computational cost for calculating the weight vector for large phased array antennas is very high, which make it difficult for real-time applications. To address this problem, a two-dimensional (2-D) adaptive beamformer applicable to large planar array antennas that have low computational complexity and low training sample requirement is proposed. In the proposed method, the weight matrix is first reconstructed as a matrix that has the same or close columns and rows by utilising the special Kronecker property of the array steering matrix. Then, the weight vector is determined by adopting a bi-quadratic cost function and a bi-iterative algorithm. Experimental results show that the proposed method can achieve fairly good performance even when the training samples are small.

Effective ground stationary operational target detection is the precondition of subsequent target identification for helicopter-borne fire-controlled radar. More abundant target information could be obtained when adopting wide-band radar than traditional narrow-band one. While there exit such problem of high false alarm and poor adaptability when applying traditional detection methods. Thus, a novel ground stationary target detection method for airborne wide-band radar based on statistical characteristic is presented in this paper. By considering statistical distribution property in both range and azimuth directions, this method could distinguish the target from strong ground clutter background adaptively and effectively. Experiment results show that our algorithm not only can improve detection performance significantly but also could enhance processing efficiency.

There exists periodic modulation problem in radar echoes due to the main rotor blades periodic blockage in helicopter-borne fire-control radar which is mounted atop the main rotor mast of the helicopter. Such modulation echo induces a set of ghosts in synthetic aperture radar (SAR) image, further resulting in a poor performance of subsequent tracking and striking. To address this problem, this article proposes a method on rotor blades blockage modulation suppression for helicopter-borne SAR. By decomposing the blocked echo into the form of Fourier series in the azimuth direction, a reference function could be constructed to suppress the modulation directly by adopting an iterative approximation strategy. This method effectively avoids the complex blocked data recovery methods, and thus can be used to suppress various kinds of periodic modulation components without requiring certain distribution models. Both simulated and real-measured data are processed to demonstrate the effectiveness of the proposed algorithm.

With the imaging advantage of bistatic forward-looking synthetic aperture radar, collaborative forward-looking imaging and reconnaissance technology for manned/unmanned aerial vehicles could be performed, in which unmanned aerial vehicle can realise two-dimensional (2-D) and high-resolution imaging and further attacking targets in its straight-ahead position. However, there exists more complicated space-variance property in this special configuration than traditional mono-static SAR. Such property will lead to performance deterioration of imaging if not corrected effectively. To address this problem, 2-D frequency spectrum with high precision is first obtained based on squint minimisation method here, and then a novel-phase space-variance correction method is developed through polynomial fitting. Imaging focus performance on targets could be improved significantly with authors’ method. Several simulations for scattering targets confirm its validity.

The performance of the conventional adaptive beamformer undergoes degradation in the presence of the mutual coupling between the neighbouring elements. To eliminate the sensitivity for the MC, the dummy elements are fixed around the array. Here, the authors demonstrate the optimal layers of auxiliary elements for uniform rectangular array (URA) in the case of the specific MC model and give the concrete theoretical proof. The corresponding derivation proves that only one layer of auxiliary elements is needed to tackle with the MC effect, and the output SINR and beampattern are improved by means of the proposed method for URA. Finally, the simulation results have shown the effectiveness of authors' method.

In this paper, we proposed an adaptive generalized displaced phased center antenna (AGDPCA) algorithm for clutter suppression in airborne radar from a viewpoint of a two-dimensional pulse-to-pulse canceller. First, the clutter model and signal model are given in matrix-vector form, and this leads naturally to the design of a two-dimensional (2-D) two-pulse (2-P) canceller and the GDPCA algorithm formulation. Second, the AGDPCA algorithm is developed by dynamically estimating the 2-D 2-P canceller from the received data. Third, the 2-D 2-P canceller is extended to 2-D multi-pulse canceller to improve the moving target detection performance in AGDPCA algorithm. The effectiveness of the proposed methods is tested via several experiments.