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
Classical localization methods use Cartesian or Polar coordinates, which require a priori range information to determine whether to estimate position or to only find bearings. The modified polar representation (MPR) u...Classical localization methods use Cartesian or Polar coordinates, which require a priori range information to determine whether to estimate position or to only find bearings. The modified polar representation (MPR) unifies near-field and farfield models, alleviating the thresholding effect. Current localization methods in MPR based on the angle of arrival (AOA) and time difference of arrival (TDOA) measurements resort to semidefinite relaxation (SDR) and Gauss-Newton iteration, which are computationally complex and face the possible diverge problem. This paper formulates a pseudo linear equation between the measurements and the unknown MPR position,which leads to a closed-form solution for the hybrid TDOA-AOA localization problem, namely hybrid constrained optimization(HCO). HCO attains Cramér-Rao bound (CRB)-level accuracy for mild Gaussian noise. Compared with the existing closed-form solutions for the hybrid TDOA-AOA case, HCO provides comparable performance to the hybrid generalized trust region subproblem (HGTRS) solution and is better than the hybrid successive unconstrained minimization (HSUM) solution in large noise region. Its computational complexity is lower than that of HGTRS. Simulations validate the performance of HCO achieves the CRB that the maximum likelihood estimator (MLE) attains if the noise is small, but the MLE deviates from CRB earlier.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
针对水下目标被动定位中传感器位置误差带来的定位精度不高的问题,提出了一种基于两步最小二乘的到达时间差波达方向(time difference of arrival-direction of arrival,TDOA-DOA)目标定位算法。首先,构建TDOA-DOA理想化无误差模型,并...针对水下目标被动定位中传感器位置误差带来的定位精度不高的问题,提出了一种基于两步最小二乘的到达时间差波达方向(time difference of arrival-direction of arrival,TDOA-DOA)目标定位算法。首先,构建TDOA-DOA理想化无误差模型,并利用最小二乘算法对目标位置进行粗估计。其次,考虑测量误差和传感器位置误差,构建目标定位误差和传感器位置的联合方程,并利用加权最小二乘求解。最后,利用目标定位误差对目标位置粗估计值进行修正,得到更精确的定位结果。仿真实验表明,所提算法可对目标位置和传感器位置进行联合估计,相较于已有算法具有更高的定位精度,更适用于传感器位置存在误差情况下的水下目标定位。展开更多
For the frequency difference of arrival (FDOA) esti-mation in passive location, this paper transforms the frequency difference estimation into the radial velocity difference estimation, which is difficult to achieve...For the frequency difference of arrival (FDOA) esti-mation in passive location, this paper transforms the frequency difference estimation into the radial velocity difference estimation, which is difficult to achieve a high accuracy due to the mismatch between the sampling period and the pulse repetition interval. The proposed algorithm firstly estimates the point-in-time that each pulse arrives at two receivers accurately. Secondly two time of arrival (TOA) sequences are subtracted. And final y the radial ve-locity difference of a target relative to two stations with the least square method is estimated. This algorithm only needs accurate estimation of the time delay between pulses and is not influenced by parameters such as frequency and modulation mode. It avoids transmitting a large amount of data between two stations in real time. Simulation results corroborate that the performance is bet-ter than the arithmetic average of the Cramer-Rao lower bound (CRLB) for monopulse under suitable conditions.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
To improve the estimation accuracy,a novel time delay estimation(TDE)method based on the closed-form offset compensation is proposed.Firstly,we use the generalized cross-correlation with phase transform(GCC-PHAT)metho...To improve the estimation accuracy,a novel time delay estimation(TDE)method based on the closed-form offset compensation is proposed.Firstly,we use the generalized cross-correlation with phase transform(GCC-PHAT)method to obtain the initial TDE.Secondly,a signal model using normalized cross spectrum is established,and the noise subspace is extracted by eigenvalue decomposition(EVD)of covariance matrix.Using the orthogonal relation between the steering vector and the noise subspace,the first-order Taylor expansion is carried out on the steering vector reconstructed by the initial TDE.Finally,the offsets are compensated via simple least squares(LS).Compared to other state-of-the-art methods,the proposed method significantly reduces the computational complexity and achieves better estimation performance.Experiments on both simulation and real-world data verify the efficiency of the proposed approach.展开更多
提出了一种基于到达时间(time of arrival,TOA)和到达时间差(time difference of arrival,TDOA)的空中运动平台对目标高精度三维定位的无源定位方法。该方法使用3个辅站信号到空中运动平台的TOA以及辅站位置确定空中运动平台自身的位置...提出了一种基于到达时间(time of arrival,TOA)和到达时间差(time difference of arrival,TDOA)的空中运动平台对目标高精度三维定位的无源定位方法。该方法使用3个辅站信号到空中运动平台的TOA以及辅站位置确定空中运动平台自身的位置,然后依据目标散射回波到达各个辅站与空中运动平台的TDOA确定目标的位置。分析了三维TDOA目标定位模糊产生的原因,提出了一种无模糊的高精度TDOA目标位置求解算法。仿真结果表明,该算法比经典的TDOA定位算法精度高,而且不存在定位模糊,从而验证了该空中运动平台对目标进行无源定位方法的有效性以及正确性。展开更多
本文针对Ho提出的基于TDOA(Time Difference of Arrival)与GROA(Gain Ratio of Arrival)信号源定位的代数闭式解,提出两种偏差消减方法.首先对其闭式解偏差进行了推导,然后给出BiasRed法与BiasSub法两种偏差消减算法,BiasSub法从Ho给出...本文针对Ho提出的基于TDOA(Time Difference of Arrival)与GROA(Gain Ratio of Arrival)信号源定位的代数闭式解,提出两种偏差消减方法.首先对其闭式解偏差进行了推导,然后给出BiasRed法与BiasSub法两种偏差消减算法,BiasSub法从Ho给出的解中直接减去期望偏差,BiasRed法通过分析误差表达方程并引入二次约束来提升定位估计精度;分析表明两种方法均可针对远距离信号源,在较小高斯误差情况下有效消减定位偏差,BiasRed法可将偏差降低到最大似然估计算法的水平;计算机仿真分析验证了所提算法的性能.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 (62101359)Sichuan University and Yibin Municipal People’s Government University and City Strategic Cooperation Special Fund Project (2020CDYB-29)+1 种基金the Science and Technology Plan Transfer Payment Project of Sichuan Province (2021ZYSF007)the Key Research and Development Program of Science and Technology Department of Sichuan Province (2020YFS0575,2021KJT0012-2 021YFS-0067)。
文摘Classical localization methods use Cartesian or Polar coordinates, which require a priori range information to determine whether to estimate position or to only find bearings. The modified polar representation (MPR) unifies near-field and farfield models, alleviating the thresholding effect. Current localization methods in MPR based on the angle of arrival (AOA) and time difference of arrival (TDOA) measurements resort to semidefinite relaxation (SDR) and Gauss-Newton iteration, which are computationally complex and face the possible diverge problem. This paper formulates a pseudo linear equation between the measurements and the unknown MPR position,which leads to a closed-form solution for the hybrid TDOA-AOA localization problem, namely hybrid constrained optimization(HCO). HCO attains Cramér-Rao bound (CRB)-level accuracy for mild Gaussian noise. Compared with the existing closed-form solutions for the hybrid TDOA-AOA case, HCO provides comparable performance to the hybrid generalized trust region subproblem (HGTRS) solution and is better than the hybrid successive unconstrained minimization (HSUM) solution in large noise region. Its computational complexity is lower than that of HGTRS. Simulations validate the performance of HCO achieves the CRB that the maximum likelihood estimator (MLE) attains if the noise is small, but the MLE deviates from CRB earlier.
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.
文摘针对水下目标被动定位中传感器位置误差带来的定位精度不高的问题,提出了一种基于两步最小二乘的到达时间差波达方向(time difference of arrival-direction of arrival,TDOA-DOA)目标定位算法。首先,构建TDOA-DOA理想化无误差模型,并利用最小二乘算法对目标位置进行粗估计。其次,考虑测量误差和传感器位置误差,构建目标定位误差和传感器位置的联合方程,并利用加权最小二乘求解。最后,利用目标定位误差对目标位置粗估计值进行修正,得到更精确的定位结果。仿真实验表明,所提算法可对目标位置和传感器位置进行联合估计,相较于已有算法具有更高的定位精度,更适用于传感器位置存在误差情况下的水下目标定位。
基金supported by the National Natural Science Foundationof China(61201208)
文摘For the frequency difference of arrival (FDOA) esti-mation in passive location, this paper transforms the frequency difference estimation into the radial velocity difference estimation, which is difficult to achieve a high accuracy due to the mismatch between the sampling period and the pulse repetition interval. The proposed algorithm firstly estimates the point-in-time that each pulse arrives at two receivers accurately. Secondly two time of arrival (TOA) sequences are subtracted. And final y the radial ve-locity difference of a target relative to two stations with the least square method is estimated. This algorithm only needs accurate estimation of the time delay between pulses and is not influenced by parameters such as frequency and modulation mode. It avoids transmitting a large amount of data between two stations in real time. Simulation results corroborate that the performance is bet-ter than the arithmetic average of the Cramer-Rao lower bound (CRLB) for monopulse under suitable conditions.
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 in part by National Key R&D Program of China under Grants 2020YFB1807602 and 2020YFB1807600National Science Foundation of China(61971217,61971218,61631020,61601167)+1 种基金the Fund of Sonar Technology Key Laboratory(Range estimation and location technology of passive target viamultiple array combination),Jiangsu Planned Projects for Postdoctoral Research Funds(2020Z013)China Postdoctoral Science Foundation(2020M681585).
文摘To improve the estimation accuracy,a novel time delay estimation(TDE)method based on the closed-form offset compensation is proposed.Firstly,we use the generalized cross-correlation with phase transform(GCC-PHAT)method to obtain the initial TDE.Secondly,a signal model using normalized cross spectrum is established,and the noise subspace is extracted by eigenvalue decomposition(EVD)of covariance matrix.Using the orthogonal relation between the steering vector and the noise subspace,the first-order Taylor expansion is carried out on the steering vector reconstructed by the initial TDE.Finally,the offsets are compensated via simple least squares(LS).Compared to other state-of-the-art methods,the proposed method significantly reduces the computational complexity and achieves better estimation performance.Experiments on both simulation and real-world data verify the efficiency of the proposed approach.
文摘提出了一种基于到达时间(time of arrival,TOA)和到达时间差(time difference of arrival,TDOA)的空中运动平台对目标高精度三维定位的无源定位方法。该方法使用3个辅站信号到空中运动平台的TOA以及辅站位置确定空中运动平台自身的位置,然后依据目标散射回波到达各个辅站与空中运动平台的TDOA确定目标的位置。分析了三维TDOA目标定位模糊产生的原因,提出了一种无模糊的高精度TDOA目标位置求解算法。仿真结果表明,该算法比经典的TDOA定位算法精度高,而且不存在定位模糊,从而验证了该空中运动平台对目标进行无源定位方法的有效性以及正确性。
文摘本文针对Ho提出的基于TDOA(Time Difference of Arrival)与GROA(Gain Ratio of Arrival)信号源定位的代数闭式解,提出两种偏差消减方法.首先对其闭式解偏差进行了推导,然后给出BiasRed法与BiasSub法两种偏差消减算法,BiasSub法从Ho给出的解中直接减去期望偏差,BiasRed法通过分析误差表达方程并引入二次约束来提升定位估计精度;分析表明两种方法均可针对远距离信号源,在较小高斯误差情况下有效消减定位偏差,BiasRed法可将偏差降低到最大似然估计算法的水平;计算机仿真分析验证了所提算法的性能.