Finding optimal trajectory points for TDOA/FDOA geo-location sensors

Ran Ren, M. Fowler, N. Wu
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引用次数: 15

Abstract

In emitter geo-location estimation systems, it is well known that the geometry between sensors and the emitter can seriously impact the accuracy of the location estimate. Here we consider a case where a set of sensors is tasked to perform a sequence of location estimates on an emitter as the sensors progress throughout their trajectories. The goal is to select the trajectories so as to optimally improve the location estimate at each step in the sequence. To build the optimal trajectories, the aircraft, at their current locations, need to know their optimal next states at the time of next estimation, under the constraint of a reachable set due to limited reachable velocity or thrust. In this paper, we propose a one-step method to tackle the optimal next state(ONS) problem using the Particle Swarm Optimization(PSO) by solving the optimal amount of applied thrust along the flying trajectories. Simulation results show that the proposed method dramatically improves the estimation accuracy along the flying trajectories, compared to the random walk and constant velocity scheme. We also show that the estimation accuracy performance is also insensitive to the problem dimensionality.
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TDOA/FDOA地理定位传感器最优轨迹点求解
在发射器地理位置估计系统中,传感器与发射器之间的几何形状会严重影响位置估计的精度。在这里,我们考虑一种情况,其中一组传感器的任务是在传感器沿着其轨迹前进时对发射器执行一系列位置估计。目标是选择轨迹,以最优地改善序列中每一步的位置估计。为了构建最优轨迹,飞机在当前位置需要知道下一次估计时的最优下一状态,在可达集约束下,由于可达速度或推力有限。本文提出了一种利用粒子群算法(PSO)一步求解最优下一状态(ONS)问题的方法,该方法通过求解沿飞行轨迹施加的最优推力量来实现。仿真结果表明,与随机漫步和等速方案相比,该方法显著提高了沿飞行轨迹的估计精度。我们还表明,估计精度性能对问题维数也不敏感。
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