基于神經(jīng)網(wǎng)絡(luò)的ML方向估計
THE ML BEARING ESTIMATION BY USE OF NEURAL NETWORKS
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摘要: 本文提出一種用于最大似然(ML)方向估計的神經(jīng)網(wǎng)絡(luò)模型。理論分析和模擬結(jié)果表明,這種網(wǎng)絡(luò)一般可以在電路的時常數(shù)數(shù)量級內(nèi)給出目標方向的ML估計值,而且網(wǎng)絡(luò)結(jié)構(gòu)和參數(shù)固定,陣列陣元輸入直接作為網(wǎng)絡(luò)的輸入而無需任何運算。因此這種網(wǎng)絡(luò)非常適用于實時處理。這為實時實現(xiàn)目標的精確定位提供了一條新途徑。
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關(guān)鍵詞:
- 信號處理; 方向估計; 神經(jīng)網(wǎng)絡(luò); 最大似然
Abstract: A neural network to implement the maximum likelihood bearing estimation algorithm in real time is proposed. Both analysis and simulation show that this neural network is guaranteed to be stable and to provide the maximum likelihood bearing estimation within an elapsed time of only a few characteristic time constants of the network. As a result, this proposed neural network is satisfactory for real time bearing estimation. -
I. Ziskind, M. Wax, IEEE Trans. on ASSP, ASSP-36(1988)4,1553-1560.[2]R. O. Schmidt, IEEE Trans. on AP, AP-34(1986)3, 276-280.[3]M. Kaveh, A. J. Baraleu, IEEE Trans.on ASSP, ASSP-34(1986)2, 331-341.[4]M. P. Kennedy, L. O. Chua, IEEE Trans. on CAS, CAS-34(1987)2, 210-214.[5]M. P. Kennedy, L. O. Chua, IEEE Trans. on CAS, CAS-35(1988)5, 554-562.[6]R. Rastogi et al., Array Signal Processing with Interconnected Neuron-like Elements, ICASSP, Texas, (1987), pp. 2328-2331.[7]S. K. Chapman, T. S. Durral, Bearing Estimation Using Neural Networks, ICASSP, New York, (1988), pp.1483-1486. -
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