Doa Estimation And The Related Noise Filtering Method

The coherence and Signal to Noise Ratio (SNR) are always attractive on the study of direction-of-arrival (DOA) estimation, because they can make the performance of some algorithms declined or even lost. The coherence disables traditional algorithms such as multiple signal classification (MUSIC). The key reason is that it leads to the deficient-rank of covariance matrix of information source. When SNR lowers, it is difficult to distinguish the primary and secondary eigenvalue after the decomposition of eigenvalues of the array covariance matrix because of that. And it will also lead to the dividing fault of signal and noise subspace partition.Aiming at the situation of coherent, people often remove the coherence influence of coherent information source based the angle of decoherence by all means. The research results show that it can solve the above problems after direct decoherence. But it often needs processes of space smooth and so on. So in the same scale of problems, it not only increases the quantity of antenna array, but also increases the burden of hardware and the cost. Imagine if we can reduce the noise in accomplishing the decoherence process, it can not only solve the trouble of coherence, still can not increase the burden of hardware. So, the engineering application of algorithms will be greatly improved. Based on this, this paper puts forward a novel noise filtering method of DOA estimation under low SNR when the received signal sources are coherent or partially coherent. The proposed method can make a contribution to the noise filtering and reduce the cost of hardware to greatly improve the performance of algorithms in DOA estimation. In the only additive white noise environment, the rank of coherent signals covariance matrix is not full according to that. Each determinant of the diagonal matrices is equal to zero, and we have related equations which correspond to the determinants. By resolving the determinant equations, we can obtain new diagonal elements which do not involve the noise components. Then, through substituting the new diagonal elements for original diagonal elements (i.e. diagonal loading processing), we can obtain the new array covariance matrix without noise components. It means the influence of white noise has been removed. The simulation results can confirm the validity of the method and promote the effect visually.In an ideal situation, if only the interference of additive white noise is existed, the SNR can be small enough when the records of the sampled signal are enough long. That means this method can improve the anti-jamming performance. In fact, when the received signal is fully coherent or partially coherent, all other DOA algorithms based on array covariance matrix can firstly take advantage of this method to preprocess to filter noise or restrain the effect of white noise. After pre-process, the performance of the algorithm and the solving accuracy of the DOA estimation have been improved. From the perspective of this method’s implementation scheme, on the one hand this method increases little calculation amount, on the other hand it doesn’t increase much cost. So we can say that it meets the basic requirements of low cost and high performance in engineering.