Sensor Selection Method for TDOA Passive Localization
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摘要:
该文主要研究一种面向到达时间差(TDOA)被动定位的定位节点选择方法。首先，通过经典的闭式解析算法将TDOA非线性方程转化为伪线性方程，并使用位置误差的协方差矩阵来度量定位精度。其次，在可用节点数量给定的条件下，在数学上将定位节点选择问题转化为最小化位置误差协方差矩阵的迹这一非凸优化问题。然后，将非凸优化问题凸松弛并化为半正定规划问题，从而快速有效地求解出最优的定位节点组合。仿真结果表明，所提节点优选方法的性能非常接近穷尽搜索方法，而且克服了穷尽搜索方法运算复杂度高、时效性差的不足，从而验证了所提方法的有效性。
Abstract:This paper focuses on the sensor selection optimization problem in Time Difference Of Arrival (TDOA) passive localization scenario. Firstly, the localization accuracy metric is given by the error covariance matrix of classical closed-form solution, which is introduced to convert the TDOA nonlinear equations into pseudo linear equations. Secondly, the problem of sensor selection can be mathematically transformed into the non-convex optimization problem, to minimize the trace of localization error covariance matrix under the condition that the number of active sensors is given. Then, the non-convex optimization problem is relaxed and transformed into a positive semi-definite programming problem so that the optimal subset of positioning nodes can be solved quickly and effectively. Simulation results validate that the performance of proposed sensor selection method is very close to the exhausted-search method, and overcomes the shortcomings of the high computation complexity and poor timeliness of the exhausted-search method.
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