摘要
传统目标跟踪算法首先通过采样信号估计时延或多普勒等参数,然后利用这些参数构成的跟踪方程获得目标运动轨迹,这种两步跟踪模式存在位置信息损失、误差累积等问题,跟踪精度仍有待提高。针对此问题,提出一种利用数据域采样信号,基于时延和多普勒信息的直接跟踪算法。该算法利用多个观测站的接收信号,首先建立一个基于连续时间和多普勒信息的直接跟踪模型;然后基于进化粒子滤波算法,对所提跟踪模型进行迭代求解,提高算法计算效率,实现对运动目标的快速高精度跟踪;最后,针对所提模型,推导了目标直接跟踪的克拉美罗下界(Cramer-Rao lower bound,CRLB)递归求解方法,给出了算法的跟踪误差下限。仿真实验表明,与现有跟踪算法相比,所提算法跟踪精度更高,收敛速度更快,尤其在低信噪比条件下更能逼近CRLB。
The traditional tracking algorithms measure the positional parameters such as the time of arrival(TOA)and Doppler shift.In the first step,and in the second step use these parameters to estimate the trajectory of the transmitter.Because of the position information loss and error accumulation,the two-step method is falling to get the best tracking performance.In order to solve this problem,a direct trajectory determination algorithm based on the evolutionary particle filter is proposed,which proves to be more precise for weak signals than the conventional approach.The algorithm exploits the TOA and Doppler shift contained in the sampled signals to establish a direct tracking model based on continuous time information,and then uses the evolutionary particle filter to solve the problem of high computation load.The last but important result is a derivation of closed-form expressions of the Cramer-Rao lower bound(CRLB).The simulation results show that,the algorithm proposed in this paper outperforms the traditional algorithms with more accurate results and higher computational efficiency.Especially in the low signal-to-noise ratio,it is more close to the CRLB.
作者
逯志宇
巴斌
任衍青
王大鸣
LU Zhiyu;BA Bin;REN Yanqing;WANG Daming(College of Information System Engineering,Information Engineering University,Zhengzhou 450001,China)
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2018年第5期968-975,共8页
Systems Engineering and Electronics
基金
国家自然科学基金(61401513)资助课题
关键词
直接跟踪
粒子滤波
到达时间
克拉美罗下界
direct trajectory determination
particle filter
time of arrival(TOA)
Cramer-Rao lower bound(CRLB)