基于联合双机MUSIC的多目标无源定位算法

Multi-target Passive Localization Based on Dual Station Joint MUSIC Algorithm

  • 摘要: 在无源定位中,基于角度信息的双机协同定位方法具有参数少、精度高和灵活性好等优点。但在辐射源日益密集的战场环境中,对多个目标实施定位时,通常将双机观测到的信息分别匹配并联合方程求解每个目标的位置,容易出现匹配错误、定位模糊问题。本文提出了一种双站联合MUSIC角度估计算法,通过降维投影的方法减少了谱函数和谱峰搜索的计算量,可以获得同一目标测向线匹配结果,并获得更高的测角精度。在定位解算中,利用经典的最小二乘法解算目标位置。仿真结果表明,对慢速多目标,相比匹配测向法,本文所提算法具有更高的定位精度。

     

    Abstract: In passive positioning, dual-aircraft co-localization methods based on angle information have some advantages of less parameters, higher precision and better flexibility than conventional methods. However, in the battlefield with density increasing radiation sources, matching errors and positioning blur always occurs while signal matching and equation combining to solve the final positioning of multiple targets. In this paper, a dual-station joint MUSIC angle estimation algorithm is proposed. Then a dimensionality reduction projection algorithm is exploited to reduce the computation of spectral function calculation and spectrum peak searching. Finally, the direction-finding line matching results of same targets are directly achieved, based on which location results with higher angle measurement accuracy can be obtained. In the positioning solution, the target position is solved by the ordinary least squares method. Simulation results show that the proposed algorithm has higher positioning accuracy than match-AOA methods for slow multiple targets.

     

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