Iterative algorithm of steered minimum variance and its application in weak targets detection |
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| Authors: | Dai-zhu Zhu Guan-fang Li Jun-ying Hui Yang Chen Wen-hua Huang |
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| Institution: | [1]School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiaotong University, Shanghai 200240, China [2]Shanghai Marine Electronic Equipment Research Institute, Shanghai 201108, China [3]National Laboratory of Underwater Acoustic Technology, Harbin Engineering University, Harbin 150001, China [4]Jiangsu Automation Research Institute of China Shipbuilding Industry Corporation, Lianyungang 222006, Jiangsu, China |
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| Abstract: | The steered covariance matrix (STCM) and its inverse matrix should be calculated in each beam for steered minimum variance
(STMV). The inverse matrix needs complex computation and restricts its application in engineering. Combining the integration
character of one-phase regressive filter with the iterative formula of inverse matrix, an STMV iterative algorithm is proposed.
The computational cost of the iterative algorithm is reduced approximately to be 2/M times of the original one when there are M sensors, and is more advantaged for the realization of the algorithm in real time. Simulation results show that the STMV
iterative algorithm can preserve the characters of STMV on high azimuth resolution and weak target detection while the computational
cost reduced sharply. The analysis on sea trial data proves that the proposed algorithm can estimate each target’s azimuth
even when the source powers differ in large scales or their bearings are very approximate. |
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