A Robust Method for Mainlobe Interference Suppression Based on Distributed Array Radar

Distributed radar is composed of several sparsely deployed small aperture radars to obtain the equivalent performance with large aperture radar. It has high angle resolution and measurement accuracy， and can effectively suppress the main lobe interference by adaptive beam forming technique. However， in practical application， the non-ideal factors such as the inaccurate position of each radar and the time-frequency non-synchronization will lead to the amplitude and phase errors， which have a serious impact on the performance of distributed radar system. Moreover，the general calibration cannot meet the needs due to the extreme-long baseline of distributed radar. In this paper， a new method was proposed to compensate the amplitude and phase errors. We use the generalized inner product （GIP） method to extract the sample of the interference， and calculate the amplitude and phase errors by the Newton′s method. Then the minimum variance distortionless （MVDR） beamformer is used to suppress the mainlobe interference. At last， simulations are performed to verify the proposed method in this paper and the results show that the method can improve the performance of distributed radar in suppressing mainlobe interference in the presence of gain and phase uncertainty. Besides， the influence of the residual phase error after compensation is also analyzed.