针对多星定位系统对地面静态目标的无源定位误差分析问题,运用Fisher信息矩阵、Taylor级数、矩阵理论和统计理论,综合考虑时差、频差、卫星位置误差以及卫星速度误差,推导了到达时间差(time difference of arrival,TDOA)/到达频率差(fre...针对多星定位系统对地面静态目标的无源定位误差分析问题,运用Fisher信息矩阵、Taylor级数、矩阵理论和统计理论,综合考虑时差、频差、卫星位置误差以及卫星速度误差,推导了到达时间差(time difference of arrival,TDOA)/到达频率差(frequency difference of arrival,FDOA)联合定位误差克拉美·罗界(Cramer-Rao lower bound,CRLB)的简单表达式,以及三星单独TDOA定位误差的CRLB,进而给出了避免TDOA定位盲区的良好卫星构型设计的充分条件.理论分析与仿真结果表明:在单独TDOA定位场景下良好的构型能完全消除定位盲区,定位精度随主星-星下点连线与主星-副星连线的夹角逼近90°而逐渐提高;通过引入FDOA与TDOA联合定位也能有效避免定位盲区,提高定位精度.展开更多
针对目前时差定位/频差定位混合无源定位算法存在的定位均方根误差(root mean square error,RMSE)和定位偏差适应测量噪声能力差的问题,提出一种基于泰勒级数展开的非完全约束加权最小二乘法。首先将无源定位问题转化为二次规划问题,简...针对目前时差定位/频差定位混合无源定位算法存在的定位均方根误差(root mean square error,RMSE)和定位偏差适应测量噪声能力差的问题,提出一种基于泰勒级数展开的非完全约束加权最小二乘法。首先将无源定位问题转化为二次规划问题,简化约束条件,应用拉格朗日乘子法求解目标定位的值。然后将得到的解在原约束条件下进行泰勒级数展开,利用获得的结果进一步优化解析解。计算机仿真对比了所提方法和两步加权最小二乘法(two-stage weighted least squares,TSWLS)、改进的约束加权最小二乘法(constrained weighted least squares,CWLS)、基于定位误差修正方法的定位性能,所提算法在兼顾实时性的同时,RMSE和定位偏差均低于TSWLS、CWLS、基于定位误差修正方法。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
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
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
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
文摘针对多星定位系统对地面静态目标的无源定位误差分析问题,运用Fisher信息矩阵、Taylor级数、矩阵理论和统计理论,综合考虑时差、频差、卫星位置误差以及卫星速度误差,推导了到达时间差(time difference of arrival,TDOA)/到达频率差(frequency difference of arrival,FDOA)联合定位误差克拉美·罗界(Cramer-Rao lower bound,CRLB)的简单表达式,以及三星单独TDOA定位误差的CRLB,进而给出了避免TDOA定位盲区的良好卫星构型设计的充分条件.理论分析与仿真结果表明:在单独TDOA定位场景下良好的构型能完全消除定位盲区,定位精度随主星-星下点连线与主星-副星连线的夹角逼近90°而逐渐提高;通过引入FDOA与TDOA联合定位也能有效避免定位盲区,提高定位精度.
文摘针对目前时差定位/频差定位混合无源定位算法存在的定位均方根误差(root mean square error,RMSE)和定位偏差适应测量噪声能力差的问题,提出一种基于泰勒级数展开的非完全约束加权最小二乘法。首先将无源定位问题转化为二次规划问题,简化约束条件,应用拉格朗日乘子法求解目标定位的值。然后将得到的解在原约束条件下进行泰勒级数展开,利用获得的结果进一步优化解析解。计算机仿真对比了所提方法和两步加权最小二乘法(two-stage weighted least squares,TSWLS)、改进的约束加权最小二乘法(constrained weighted least squares,CWLS)、基于定位误差修正方法的定位性能,所提算法在兼顾实时性的同时,RMSE和定位偏差均低于TSWLS、CWLS、基于定位误差修正方法。
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.
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.
