In order to improve the accuracy and engineering feasibility of four-Satellite localization system, the frequency difference measurement is introduced to the four-Satellite TDOA (Time Difference of Arrival) localizati...In order to improve the accuracy and engineering feasibility of four-Satellite localization system, the frequency difference measurement is introduced to the four-Satellite TDOA (Time Difference of Arrival) localization algorithm. The TDOA/FDOA (Frequency Difference of Arrival) localization algorithm is used to optimize the GDOP (geometric dilution of precision) of four-Satellite localization. The simulation results show that the absolute position measurement accuracy has little influence on TDOA/FDOA localization accuracy as compared with TDOA localization. Under the same conditions, TDOA/FDOA localization has better accuracy and its GDOP shows more uniform distribution in diamond configuration case. The localization accuracy of four-Satellite TDOA/FDOA is better than the localization accuracy of four-Satellite TDOA.展开更多
As an important application research topic of the intelligent aviation multi-station, collaborative detecting must overcome the problem of scouting measurement with status of 'fragmentation', and the NP-hardne...As an important application research topic of the intelligent aviation multi-station, collaborative detecting must overcome the problem of scouting measurement with status of 'fragmentation', and the NP-hardness problem of matching association between target and measurement in the process of scouting to data-link, which has complicated technical architecture of network construction. In this paper, taking advantage of cooperation mechanism on signal level in the aviation multi-station sympathetic network, a method of obtaining target time difference of arrival (TDOA) measurement using multi-station collaborative detecting based on time-frequency association is proposed. The method can not only achieve matching between target and its measurement, but also obtain TDOA measurement by further evolutionary transaction through refreshing sequential pulse time of arrival (TOA) measurement matrix for matching and correlating. Simulation results show that the accuracy of TDOA measurement has significant superiority over TOA, and detection probability of false TDOA measurement introduced by noise and fake measurement can be reduced effectively.展开更多
The source location based on the hybrid time difference of arrival(TDOA)/frequency difference of arrival(FDOA) is a basic problem in wireless sensor networks, and the layout of sensors in the hybrid TDOA/FDOA position...The source location based on the hybrid time difference of arrival(TDOA)/frequency difference of arrival(FDOA) is a basic problem in wireless sensor networks, and the layout of sensors in the hybrid TDOA/FDOA positioning will greatly affect the accuracy of positioning. Using unmanned aerial vehicle(UAV) as base stations, by optimizing the trajectory of the UAV swarm, an optimal positioning configuration is formed to improve the accuracy of the target position and velocity estimation. In this paper, a hybrid TDOA/FDOA positioning model is first established, and the positioning accuracy of the hybrid TDOA/FDOA under different positioning configurations and different measurement errors is simulated by the geometric dilution of precision(GDOP) factor. Second, the Cramer-Rao lower bound(CRLB) matrix of hybrid TDOA/FDOA location under different moving states of the target is derived theoretically, the objective function of the track optimization is obtained, and the track of the UAV swarm is optimized in real time. The simulation results show that the track optimization effectively improves the accuracy of the target position and velocity estimation.展开更多
采用频率测量实现目标定位具有成本低、可靠性高的特点,仅利用到达频率差(frequency difference of arrival,FDOA)测量,提出了一种静态目标位置的精确定位方法。针对所建立的频率测量方程的高度非线性这一问题,通过引入辅助变量,将其转...采用频率测量实现目标定位具有成本低、可靠性高的特点,仅利用到达频率差(frequency difference of arrival,FDOA)测量,提出了一种静态目标位置的精确定位方法。针对所建立的频率测量方程的高度非线性这一问题,通过引入辅助变量,将其转化为矩阵形式的伪线性方程;然后利用半正定松弛(semi-definite relaxation,SDR)方法将非凸的加权最小二乘(weighted least square,WLS)问题松弛为半正定规划(semidefinite programming,SDP)问题,从而进一步精确估计未知变量;最后对所提出方法的均方根误差(rootmean-square error,RMSE)进行了分析,以验证其性能。仿真结果表明,在较低的高斯噪声水平下,所采用的半正定松弛方法的性能能够达到克拉美罗下界(Cramer-Rao lower bound,CRLB),且该算法对几何形状具有较高的鲁棒性;此外,在使用较少数量的传感器时,其RMSE性能要优于两阶段加权最小二乘(two-stage weighted least square,TSWLS)法。展开更多
鉴于无源定位技术已经成为现代信息化作战的核心技术,提出了一种新的运动多站无源时差(time difference of arrival, TDOA)频差(frequency difference of arrival, FDOA)联合定位方法去解决无源定位系统中的非线性最优化问题。通过智能...鉴于无源定位技术已经成为现代信息化作战的核心技术,提出了一种新的运动多站无源时差(time difference of arrival, TDOA)频差(frequency difference of arrival, FDOA)联合定位方法去解决无源定位系统中的非线性最优化问题。通过智能算法的启发,将优化后的基于线性递减权重和物竞天择的粒子群算法(particle swarm optimization algorithm based on linear decreasing weight and natural selection, WSPSO)与经典加权最小二乘算法(weighted least squares, WLS)相联合对目标进行跟踪定位。加权最小二乘定位算法在4个基站的情况下无法实现对辐射源的定位,所得定位结果会出现多解。而所提的运动多站联合定位算法在4个基站的条件下不存在初始目标位置估计和局部收敛等问题就能够实现辐射源的精确定位。通过大量仿真结果分析,本文所提的智能优化定位算法具有更高的目标定位精度和更稳健的定位性能,优于标准粒子群算法与优化PSO算法。展开更多
文摘In order to improve the accuracy and engineering feasibility of four-Satellite localization system, the frequency difference measurement is introduced to the four-Satellite TDOA (Time Difference of Arrival) localization algorithm. The TDOA/FDOA (Frequency Difference of Arrival) localization algorithm is used to optimize the GDOP (geometric dilution of precision) of four-Satellite localization. The simulation results show that the absolute position measurement accuracy has little influence on TDOA/FDOA localization accuracy as compared with TDOA localization. Under the same conditions, TDOA/FDOA localization has better accuracy and its GDOP shows more uniform distribution in diamond configuration case. The localization accuracy of four-Satellite TDOA/FDOA is better than the localization accuracy of four-Satellite TDOA.
基金supported by the National Natural Science Foundation of China(61472443)the Basic Research Priorities Program of Shaanxi Province Natural Science Foundation of China(2013JQ8042)
文摘As an important application research topic of the intelligent aviation multi-station, collaborative detecting must overcome the problem of scouting measurement with status of 'fragmentation', and the NP-hardness problem of matching association between target and measurement in the process of scouting to data-link, which has complicated technical architecture of network construction. In this paper, taking advantage of cooperation mechanism on signal level in the aviation multi-station sympathetic network, a method of obtaining target time difference of arrival (TDOA) measurement using multi-station collaborative detecting based on time-frequency association is proposed. The method can not only achieve matching between target and its measurement, but also obtain TDOA measurement by further evolutionary transaction through refreshing sequential pulse time of arrival (TOA) measurement matrix for matching and correlating. Simulation results show that the accuracy of TDOA measurement has significant superiority over TOA, and detection probability of false TDOA measurement introduced by noise and fake measurement can be reduced effectively.
基金supported by the National Natural Science Foundation of China (61502522)Equipment Pre-Research Field Fund(JZX7Y20190253036101)+1 种基金Equipment Pre-Research Ministry of Education Joint Fund (6141A02033703)Hubei Provincial Natural Scie nce Foundation (2019CFC897)。
文摘The source location based on the hybrid time difference of arrival(TDOA)/frequency difference of arrival(FDOA) is a basic problem in wireless sensor networks, and the layout of sensors in the hybrid TDOA/FDOA positioning will greatly affect the accuracy of positioning. Using unmanned aerial vehicle(UAV) as base stations, by optimizing the trajectory of the UAV swarm, an optimal positioning configuration is formed to improve the accuracy of the target position and velocity estimation. In this paper, a hybrid TDOA/FDOA positioning model is first established, and the positioning accuracy of the hybrid TDOA/FDOA under different positioning configurations and different measurement errors is simulated by the geometric dilution of precision(GDOP) factor. Second, the Cramer-Rao lower bound(CRLB) matrix of hybrid TDOA/FDOA location under different moving states of the target is derived theoretically, the objective function of the track optimization is obtained, and the track of the UAV swarm is optimized in real time. The simulation results show that the track optimization effectively improves the accuracy of the target position and velocity estimation.
文摘采用频率测量实现目标定位具有成本低、可靠性高的特点,仅利用到达频率差(frequency difference of arrival,FDOA)测量,提出了一种静态目标位置的精确定位方法。针对所建立的频率测量方程的高度非线性这一问题,通过引入辅助变量,将其转化为矩阵形式的伪线性方程;然后利用半正定松弛(semi-definite relaxation,SDR)方法将非凸的加权最小二乘(weighted least square,WLS)问题松弛为半正定规划(semidefinite programming,SDP)问题,从而进一步精确估计未知变量;最后对所提出方法的均方根误差(rootmean-square error,RMSE)进行了分析,以验证其性能。仿真结果表明,在较低的高斯噪声水平下,所采用的半正定松弛方法的性能能够达到克拉美罗下界(Cramer-Rao lower bound,CRLB),且该算法对几何形状具有较高的鲁棒性;此外,在使用较少数量的传感器时,其RMSE性能要优于两阶段加权最小二乘(two-stage weighted least square,TSWLS)法。
文摘鉴于无源定位技术已经成为现代信息化作战的核心技术,提出了一种新的运动多站无源时差(time difference of arrival, TDOA)频差(frequency difference of arrival, FDOA)联合定位方法去解决无源定位系统中的非线性最优化问题。通过智能算法的启发,将优化后的基于线性递减权重和物竞天择的粒子群算法(particle swarm optimization algorithm based on linear decreasing weight and natural selection, WSPSO)与经典加权最小二乘算法(weighted least squares, WLS)相联合对目标进行跟踪定位。加权最小二乘定位算法在4个基站的情况下无法实现对辐射源的定位,所得定位结果会出现多解。而所提的运动多站联合定位算法在4个基站的条件下不存在初始目标位置估计和局部收敛等问题就能够实现辐射源的精确定位。通过大量仿真结果分析,本文所提的智能优化定位算法具有更高的目标定位精度和更稳健的定位性能,优于标准粒子群算法与优化PSO算法。
