自適應(yīng)陣列中多級(jí)維納濾波器的有效實(shí)現(xiàn)算法
Efficient Algorithms for Implementing Multistage Wiener Filter in Adaptive Arrays
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摘要: 在分析多級(jí)維納濾波器實(shí)現(xiàn)算法的基礎(chǔ)上，證明了由相關(guān)相減算法實(shí)現(xiàn)的多級(jí)維納濾波器是一種酉多級(jí)維納濾波器，與Goldstein、Reed和Scharf提出的原始實(shí)現(xiàn)算法相比，酉多級(jí)維納濾波器具有更好的降秩性能。該文對(duì)相關(guān)相減算法中的阻塞矩陣進(jìn)行改進(jìn)，使多級(jí)維納濾波器前向遞推中觀測(cè)數(shù)據(jù)向量的維數(shù)逐步降低，且同樣能應(yīng)用于相關(guān)相減算法結(jié)構(gòu)。新的實(shí)現(xiàn)算法在進(jìn)一步降低計(jì)算量的同時(shí)，得到與相關(guān)相減算法幾乎相同的性能。仿真結(jié)果證明了該算法的有效性。
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關(guān)鍵詞:
- 自適應(yīng)陣列;多級(jí)維納濾波器;降秩處理
Abstract: Based on the analysis of the algorithms for implementing Multistage Wiener Filter (MWF), the MWF implemented by the Correlation Subtraction Algorithm (CSA) is proved to be an Unitary MWF (UMWF). The rank reduction performance of UMWF is superior to the original MWF proposed by Goldstein, Reed, and Scharf. In this paper, the block matrixes in the CSA are modified to reduce the size of the observation data vectors step by step in the forward recursion of MWF. The modified block matrixes can also be used in the CSA architecture. The new implementing algorithm needs a lower computation complexity, while keeping almost the same performance as the CSA. The validity of the proposed algorithm is proved by the simulation results. -
Goldstein J S, Reed I S, Scharf L L. A multistage representation of the Wiener filter based on orthogonal projections[J].IEEE Trans. on Information Theory.1998, 44 (7):2943-[2]Ricks D C, Goldstein J S. Efficient architectures for implementing adaptive algorithms. Proceedings of the 2000 Antenna Applications Symposium, Allerton Park, Monticello, IL, Sept. 2000: 29.41.[3]Ricks D C, Cifuentes P G, Goldstein J S. Adaptive beamforming using multistage Wiener filter with a soft stop. Conference Record of the Thirty.Fifth Asilomar Conference on Signals, Systems Computers, Pacific Grove, CA, USA, Nov. 2001:14011.406.[4]Weippert M E, Hiemstra J D, Goldstein J S, et al.. Insights from the relationship between the multistage Wiener filter and the method of conjugate gradients. 2nd IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2002), Rosslyn VA, August 2002: 388.392.[5]Joham M, Zoltowski M D. Interpretation of the multi-stage nested Wiener filter in the Krylov subspace framework. Tech. Rep. TUM-LNS-TR-00-6, Munich University of Technology, November 2000. Also: Technical Report TR-ECE-00.51, Purdue University. -
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