A Study On Robust Radar Anti-interference Algorithm

Since the world war II, due to the urgent military needs, radar has found its wide application and development. There are many kinds of jamming signals except target signal in radars' working environment, which severely degrades radars'performance on target detection. The spatial anti-interference is by far the most commonly used anti-jamming technology. But the nonstationarity of interference signals leads to the deterioration of spatial adaptive processing performance. To solve this problem, researchers put forward robust spatial anti-interference methods, in general, all of which need to deal with receiving data of every array element. However, there are thousands of arrays elements in a modern radar system. It will be difficult for the proposed robust spatial anti-jamming methods to be applied in practical engineering if adaptive processing is used on all receiving data. On the other hand, in order to solve the contradiction between computational complexity and anti-jamming performance, the receiving data is processed by partially adaptive method in modern radar systems to reduce the cost of computation and storage. But for the processed data, there is no corresponding robust spatial anti-interference method can be used to effectively detect the target signal.In this paper, the robust anti-jamming algorithm is discussed. First the signal model used in this paper is defined, and the basic theory of adaptive beamforming is introduced, laying the foundation for the discussion in subsequent chapters; Next, this paper discusses the application of robust anti-interference methods in fully adaptive array processing, and analyzes the principle of dimension reduction in partially adaptive processing, with the intention to find the combining point between the above two theories. Finally, on the base of the foregoing analysis, two kinds of robust partially adaptive processing and a robust adaptive sidelobe cancellation processing algorithm are put forward. The relative simulation work is carried out as well.Robust adaptive anti-jamming methods, whether diagonal loading or north widing, are realized by the Hadamard product of a interference covariance matrix and a positive (semi) definite matrix, so as to decerease the eigenvalue spread of the covariance matrix it is modifying, thus enhancing the algorithm robustness. And the processing mentioned above can be viewed as the Hadamard product of a interference sample and a correspond random vector, which means to modify the interference sample. Therefore, there are two types of ways for robust partially adaptive array processing:The one is modifying receieving data with a random vector by Hadamard product, which is followed by the partially adaptive array processing algorithm. This method can be adapted to any dimension reduction or rank reduction adaptive processing, and can effectively reduce the amount of calculation while enhancing the algorithm robustness. The other is applying the partially adaptive array processing algorithm first, and then modifying processed data with a random vector by Hadamard product. This idea, effectively used in subarray partially adaptive array processing, not only can furtherly reduce the amount of calculation, but also can be applied to the scene in which only the subarray partially adaptive processed data is available. In addition, after calculating the required adaptive degree of freedom of wide notch, the notch-widening techique can be applied to the sidelobe cancellation algorithm to realize robust adaptive sidelobe cancellation algorithm. The experimental simulation results show that the robust anti-jamming algorithm of partial adaptive array processing mentioned above do produce wide notch practically wanted, and ultimately improve radars' performance on target detection.