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
By utilizing the time difference of arrival （TDOA） and frequency difference of arrival （FDOA） measurements of signals received at a number of receivers, a constrained least-square （CLS） algorithm for estimating ...By utilizing the time difference of arrival （TDOA） and frequency difference of arrival （FDOA） measurements of signals received at a number of receivers, a constrained least-square （CLS） algorithm for estimating the position and velocity of a moving source is proposed. By utilizing the Lagrange multipliers technique, the known relation between the intermediate variables and the source location coordinates could be exploited to constrain the solution. And without requiring apriori knowledge of TDOA and FDOA measurement noises, the proposed algorithm can satisfy the demand of practical applications. Additionally, on basis of con- volute and polynomial rooting operations, the Lagrange multipliers can be obtained efficiently and robustly allowing real-time imple- mentation and global convergence. Simulation results show that the proposed estimator achieves remarkably better performance than the two-step weighted least square （WLS） approach especially for higher measurement noise level.展开更多
Based on the time differences of arrival(TDOA) and frequency differences of arrival(FDOA) measurements of the given planar stationary radiation source, the joint TDOA/FDOA location algorithm which solves the location ...Based on the time differences of arrival(TDOA) and frequency differences of arrival(FDOA) measurements of the given planar stationary radiation source, the joint TDOA/FDOA location algorithm which solves the location of the target directly is proposed. Compared with weighted least squares(WLS) methods,the proposed algorithm is also suitable for well-posed conditions,and gets rid of the dependence on the constraints of Earth's surface. First of all, the solution formulas are expressed by the radial range. Then substitute it into the equation of the radial range to figure out the radial range between the target and the reference station. Finally use the solution expression of the target location to estimate the location of the target accurately. The proposed algorithm solves the problem that WLS methods have a large positioning error when the number of observation stations is not over-determined. Simulation results show the effectiveness of the proposed algorithm, including effectively increasing the positioning accuracy and reducing the number of observatories.展开更多
This paper considers the time difference of arrival(TDOA)and frequency difference of arrival(FDOA)estimation problem for joint localization using unmanned aerial vehicles(UAVs),involving range migration(RM)and Doppler...This paper considers the time difference of arrival(TDOA)and frequency difference of arrival(FDOA)estimation problem for joint localization using unmanned aerial vehicles(UAVs),involving range migration(RM)and Doppler ambiguity within observation interval.A robust estimation method based on interpolation and resampling is proposed.Specifically,the interpolation artificially increases the pulse repetition frequency(PRF).After that,the resampling eliminates the coupling between range frequency and slow time.Finally,a coherent integration step based on inverse discrete Fourier transform(IDFT)is used to achieve parameter estimation and suppress the grating lobes caused by interpolation.The proposed method could be efficiently implemented by fast Fourier transform(FFT),inverse FFT(IFFT)and non-uniform FFT(NUFFT)without parameter searching procedures.Numerical experiments indicate that the proposed method has nearly optimal anti-noise performance but much lower computational complexity than the maximum likelihood estimator,which makes it more competitive in practical applications.展开更多
为更好地解决在时间和方向测量精度低的情况下,仅利用到达频差(frequency difference of arrival,FDOA)进行定位求解的问题,对基于FDOA的无源定位算法现状和发展方向进行分析。在阐述FDOA无源定位基本原理的基础上,分析了定位问题的本...为更好地解决在时间和方向测量精度低的情况下,仅利用到达频差(frequency difference of arrival,FDOA)进行定位求解的问题,对基于FDOA的无源定位算法现状和发展方向进行分析。在阐述FDOA无源定位基本原理的基础上,分析了定位问题的本质和定位算法的分类方法,结合基于定位观测量数据的定位算法和接收信号直接定位法的国内外研究现状,分析了FDOA无源定位算法存在的问题,指明了基于FDOA的定位算法的未来研究方向。该研究可为基于FDOA定位算法的研究提供参考依据。展开更多
利用到达时间差(Time Difference of Arrival,TDOA)和到达频率差(Frequency Difference of Arrival,FDOA)对移动目标进行定位是现代电子战争的重要课题。传统的定位算法由于TDOA/FDOA参数与目标参数存在非线性关系,求解困难且存在初值...利用到达时间差(Time Difference of Arrival,TDOA)和到达频率差(Frequency Difference of Arrival,FDOA)对移动目标进行定位是现代电子战争的重要课题。传统的定位算法由于TDOA/FDOA参数与目标参数存在非线性关系,求解困难且存在初值与收敛性问题。为此提出一种结合两步加权最小二乘法(Two-Stage Weighted Least Squares,TSWLS)与偏差补偿的定位算法,这种结合算法先建立一组关于TDOA与FDOA的线性方程,再利用泰勒级数展开算法线性化中间变量,计算偏差值,用线性方程的解减去偏差值得到最终解,算法的解为闭式解不存在收敛问题。仿真证明,结合算法优于传统TSWLS算法,在低噪声环境下可以达到克拉美罗界(Cramér-Rao Lower Bound,CRLB),同时在大噪声环境下也能保持良好的鲁棒性,且目标距离越近,观测点阵的大小越大,定位性能越好。展开更多
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.
基金supported by the National High Technology Research and Development Program of China (863 Program) (2010AA7010422 2011AA7014061)
文摘By utilizing the time difference of arrival （TDOA） and frequency difference of arrival （FDOA） measurements of signals received at a number of receivers, a constrained least-square （CLS） algorithm for estimating the position and velocity of a moving source is proposed. By utilizing the Lagrange multipliers technique, the known relation between the intermediate variables and the source location coordinates could be exploited to constrain the solution. And without requiring apriori knowledge of TDOA and FDOA measurement noises, the proposed algorithm can satisfy the demand of practical applications. Additionally, on basis of con- volute and polynomial rooting operations, the Lagrange multipliers can be obtained efficiently and robustly allowing real-time imple- mentation and global convergence. Simulation results show that the proposed estimator achieves remarkably better performance than the two-step weighted least square （WLS） approach especially for higher measurement noise level.
基金supported by the National Natural Science Foundation of China(6140236561271300)the 13th Five-Year Weaponry PreResearch Project。
文摘Based on the time differences of arrival(TDOA) and frequency differences of arrival(FDOA) measurements of the given planar stationary radiation source, the joint TDOA/FDOA location algorithm which solves the location of the target directly is proposed. Compared with weighted least squares(WLS) methods,the proposed algorithm is also suitable for well-posed conditions,and gets rid of the dependence on the constraints of Earth's surface. First of all, the solution formulas are expressed by the radial range. Then substitute it into the equation of the radial range to figure out the radial range between the target and the reference station. Finally use the solution expression of the target location to estimate the location of the target accurately. The proposed algorithm solves the problem that WLS methods have a large positioning error when the number of observation stations is not over-determined. Simulation results show the effectiveness of the proposed algorithm, including effectively increasing the positioning accuracy and reducing the number of observatories.
基金The authors would like to acknowledge National Natural Science Foundation of China(Grant No.xxxxxx)。
文摘This paper considers the time difference of arrival(TDOA)and frequency difference of arrival(FDOA)estimation problem for joint localization using unmanned aerial vehicles(UAVs),involving range migration(RM)and Doppler ambiguity within observation interval.A robust estimation method based on interpolation and resampling is proposed.Specifically,the interpolation artificially increases the pulse repetition frequency(PRF).After that,the resampling eliminates the coupling between range frequency and slow time.Finally,a coherent integration step based on inverse discrete Fourier transform(IDFT)is used to achieve parameter estimation and suppress the grating lobes caused by interpolation.The proposed method could be efficiently implemented by fast Fourier transform(FFT),inverse FFT(IFFT)and non-uniform FFT(NUFFT)without parameter searching procedures.Numerical experiments indicate that the proposed method has nearly optimal anti-noise performance but much lower computational complexity than the maximum likelihood estimator,which makes it more competitive in practical applications.
文摘为更好地解决在时间和方向测量精度低的情况下,仅利用到达频差(frequency difference of arrival,FDOA)进行定位求解的问题,对基于FDOA的无源定位算法现状和发展方向进行分析。在阐述FDOA无源定位基本原理的基础上,分析了定位问题的本质和定位算法的分类方法,结合基于定位观测量数据的定位算法和接收信号直接定位法的国内外研究现状,分析了FDOA无源定位算法存在的问题,指明了基于FDOA的定位算法的未来研究方向。该研究可为基于FDOA定位算法的研究提供参考依据。
文摘利用到达时间差(Time Difference of Arrival,TDOA)和到达频率差(Frequency Difference of Arrival,FDOA)对移动目标进行定位是现代电子战争的重要课题。传统的定位算法由于TDOA/FDOA参数与目标参数存在非线性关系,求解困难且存在初值与收敛性问题。为此提出一种结合两步加权最小二乘法(Two-Stage Weighted Least Squares,TSWLS)与偏差补偿的定位算法,这种结合算法先建立一组关于TDOA与FDOA的线性方程,再利用泰勒级数展开算法线性化中间变量,计算偏差值,用线性方程的解减去偏差值得到最终解,算法的解为闭式解不存在收敛问题。仿真证明,结合算法优于传统TSWLS算法,在低噪声环境下可以达到克拉美罗界(Cramér-Rao Lower Bound,CRLB),同时在大噪声环境下也能保持良好的鲁棒性,且目标距离越近,观测点阵的大小越大,定位性能越好。
