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A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

机译:LPI雷达网络中用于多目标跟踪的新型传感器选择和功率分配算法

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Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI) performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI) threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance.
机译:事实证明,雷达网络比传统的单基地和双基地雷达具有许多优势。随着最新的发展,雷达网络由于其对目标跟踪的拦截(LPI)性能低而已成为有吸引力的平台。提出了一种基于LPI的雷达网络多目标跟踪联合传感器选择和功率分配算法。发现该算法可以基于目标冲激响应和反射信号之间的预定互信息(MI)阈值来最小化雷达网络的总发射功率。雷达网络系统需要MI来估计目标参数,并且可以通过估计目标状态来预测性地计算出MI。包含两个变量的传感器选择和功率分配的优化问题是非凸的,可以通过将功率分配问题与传感器选择问题分开来解决。具体而言,可以通过对每个传感器选择方案使用二分法来解决功率分配的优化问题。同样,可以通过基于分配功率的较低复杂度算法来解决传感器选择的优化问题。从仿真结果可以看出,该算法可以有效降低雷达网络的总发射功率,有利于提高LPI性能。

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