一种基于空域和频域信息的固定单站无源定位跟踪改进算法
doi: 10.3724/SP.J.1146.2006.00707
An Improved Algorithm for Single Non-moving Observer Passive Location and Tracking Based on Frequency and Spatial Measurements
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摘要: 针对无源定位必须实现快速和稳定定位跟踪的要求,本文基于辐射源信号的空域和频域信息,提出了一种对运动辐射源的固定单站无源定位跟踪改进算法。文中首先利用辐射源信号的空域和频域变化量信息,通过伪线性卡尔曼滤波算法估计出目标的速度矢量;然后利用速度矢量的估计值直接获得目标位置矢量的估计,并将其作为标准卡尔曼滤波算法的观测值进行滤波;最后通过计算机仿真验证了该方法具有较高的定位精度和较快的收敛速度。Abstract: To satisfy the requirement of high location speed and stability, the paper presents an improved algorithm for 3-D moving emitter passive location and tracking using the frequency and spatial measurements by single non-moving observer. This method firstly takes full advantage of the spatial and frequency changing information to estimate the velocity vector of the emitter via the Pseudo-Linear Kalman Filter (PLKF) algorithm, which can be used to obtain the position vector, the Kalman filter is to improve the location accuracy by taking the estimation of the position vector as measurements; the computer simulations show that the method has high location accuracy and fast convergence speed.
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