The uncertainty of observers' positions can lead to significantly degrading in source localization accuracy. This pa-per proposes a method of using self-location for calibrating the positions of observer stations in ...The uncertainty of observers' positions can lead to significantly degrading in source localization accuracy. This pa-per proposes a method of using self-location for calibrating the positions of observer stations in source localization to reduce the errors of the observer positions and improve the accuracy of the source localization. The relative distance measurements of the two coordinative observers are used for the linear minimum mean square error (LMMSE) estimator. The results of computer si-mulations prove the feasibility and effectiveness of the proposed method. With the general estimation errors of observers' positions, the MSE of the source localization with self-location calibration, which is significantly lower than that without self-location calibra-tion, is approximating to the Cramer-Rao lower bound (CRLB).展开更多
Due to the deficiencies in the conventional multiple-receiver localization syste,.ns based on direction of arrival (DOA) such as system complexity of interferometer or array and ampli- tude/phase unbalance between m...Due to the deficiencies in the conventional multiple-receiver localization syste,.ns based on direction of arrival (DOA) such as system complexity of interferometer or array and ampli- tude/phase unbalance between multiple receiving channels and constraint on antenna configuration, a new radiated source localization method using the changing rate of phase difference (CRPD) measured by a long baseline interferometer (LBI) only is studied. To solve the strictly nonlinear problem, a two-stage closed-form solution is proposed. In the first stage, the DOA and its changing rate are estimated from the CRPD of each observer by the pseudolinear least square (PLS) method, and then in the second stage, the source position and velocity are found by another PLS minimiza- tion. The bias of the algorithm caused by the correlation between the measurement matrix and the noise in the second stage is analyzed. To reduce this bias, an instrumental variable (IV) method is derived. A weighted IV estimator is given in order to reduce the estimation variance. The proposed method does not need any initial guess and the computation is small. The Cramer-Rao lower bound (CRLB) and mean square error (MSE) are also analyzed. Simulation results show that the proposed method can be close to the CRLB with moderate Gaussian measurement noise.展开更多
It is well known that the Two-step Weighted Least-Squares(TWLS) is a widely used method for source localization and sensor position refinement. For this reason, we propose a unified framework of the TWLS method for jo...It is well known that the Two-step Weighted Least-Squares(TWLS) is a widely used method for source localization and sensor position refinement. For this reason, we propose a unified framework of the TWLS method for joint estimation of multiple disjoint sources and sensor locations in this paper. Unlike some existing works, the presented method is based on more general measurement model, and therefore it can be applied to many different localization scenarios.Besides, it does not have the initialization and local convergence problem. The closed-form expression for the covariance matrix of the proposed TWLS estimator is also derived by exploiting the first-order perturbation analysis. Moreover, the estimation accuracy of the TWLS method is shown analytically to achieve the Cramér-Rao Bound(CRB) before the threshold effect takes place. The theoretical analysis is also performed in a common mathematical framework, rather than aiming at some specific signal metrics. Finally, two numerical experiments are performed to support the theoretical development in this paper.展开更多
针对海洋传感网(Ocean Sensor Networks,OSNs)中采用非协同算法单一循环地对多个水面目标节点依次定位导致的定位效率低、定位精度差等问题,提出一种基于有效集的再优化协同定位(Active Set Method based Re-Estimation Cooperative Loc...针对海洋传感网(Ocean Sensor Networks,OSNs)中采用非协同算法单一循环地对多个水面目标节点依次定位导致的定位效率低、定位精度差等问题,提出一种基于有效集的再优化协同定位(Active Set Method based Re-Estimation Cooperative Localization,ASM-RECL)算法。研究将原定位的非凸非线性问题转化为基于交替非负约束最小二乘(Alternative Nonnegative Constrained Least Squares,ANCLS)的优化问题,利用有效集法(Active Set Method,ASM)通过内外循环寻求优化问题的可行解。但ASM算法易陷入局部最优,为进一步提升解的质量,改进定位精度,基于ASM得出的可行解,应用一阶泰勒级数线性展开再次构造优化方程,最小化定位误差。此外,研究还推导得到基于协同定位的克劳美罗下界(Cooperative Localization-based Cramer-Rao Low Bound,CRLB-CL),以此作为评价标准评估提出的定位算法的有效性。仿真实验表明,在不同的条件下,ASM-RECL的定位精度较高于其他算法。展开更多
基金supported by the Fundamental Research Funds for the Central Universities(ZYGX2009J016)
文摘The uncertainty of observers' positions can lead to significantly degrading in source localization accuracy. This pa-per proposes a method of using self-location for calibrating the positions of observer stations in source localization to reduce the errors of the observer positions and improve the accuracy of the source localization. The relative distance measurements of the two coordinative observers are used for the linear minimum mean square error (LMMSE) estimator. The results of computer si-mulations prove the feasibility and effectiveness of the proposed method. With the general estimation errors of observers' positions, the MSE of the source localization with self-location calibration, which is significantly lower than that without self-location calibra-tion, is approximating to the Cramer-Rao lower bound (CRLB).
基金co-supported by the Foundation of National Defense Key Laboratory of China (No. 9140C860304)the National High Technology Research and Development Program of China (No. 2011AA7072048)
文摘Due to the deficiencies in the conventional multiple-receiver localization syste,.ns based on direction of arrival (DOA) such as system complexity of interferometer or array and ampli- tude/phase unbalance between multiple receiving channels and constraint on antenna configuration, a new radiated source localization method using the changing rate of phase difference (CRPD) measured by a long baseline interferometer (LBI) only is studied. To solve the strictly nonlinear problem, a two-stage closed-form solution is proposed. In the first stage, the DOA and its changing rate are estimated from the CRPD of each observer by the pseudolinear least square (PLS) method, and then in the second stage, the source position and velocity are found by another PLS minimiza- tion. The bias of the algorithm caused by the correlation between the measurement matrix and the noise in the second stage is analyzed. To reduce this bias, an instrumental variable (IV) method is derived. A weighted IV estimator is given in order to reduce the estimation variance. The proposed method does not need any initial guess and the computation is small. The Cramer-Rao lower bound (CRLB) and mean square error (MSE) are also analyzed. Simulation results show that the proposed method can be close to the CRLB with moderate Gaussian measurement noise.
基金co-supported by the National Natural Science Foundation of China (Nos. 61201381, 61401513 and 61772548)the China Postdoctoral Science Foundation (No. 2016M592989)+1 种基金the Self-Topic Foundation of Information Engineering University, China (No. 2016600701)the Outstanding Youth Foundation of Information Engineering University, China (No. 2016603201)
文摘It is well known that the Two-step Weighted Least-Squares(TWLS) is a widely used method for source localization and sensor position refinement. For this reason, we propose a unified framework of the TWLS method for joint estimation of multiple disjoint sources and sensor locations in this paper. Unlike some existing works, the presented method is based on more general measurement model, and therefore it can be applied to many different localization scenarios.Besides, it does not have the initialization and local convergence problem. The closed-form expression for the covariance matrix of the proposed TWLS estimator is also derived by exploiting the first-order perturbation analysis. Moreover, the estimation accuracy of the TWLS method is shown analytically to achieve the Cramér-Rao Bound(CRB) before the threshold effect takes place. The theoretical analysis is also performed in a common mathematical framework, rather than aiming at some specific signal metrics. Finally, two numerical experiments are performed to support the theoretical development in this paper.
文摘针对海洋传感网(Ocean Sensor Networks,OSNs)中采用非协同算法单一循环地对多个水面目标节点依次定位导致的定位效率低、定位精度差等问题,提出一种基于有效集的再优化协同定位(Active Set Method based Re-Estimation Cooperative Localization,ASM-RECL)算法。研究将原定位的非凸非线性问题转化为基于交替非负约束最小二乘(Alternative Nonnegative Constrained Least Squares,ANCLS)的优化问题,利用有效集法(Active Set Method,ASM)通过内外循环寻求优化问题的可行解。但ASM算法易陷入局部最优,为进一步提升解的质量,改进定位精度,基于ASM得出的可行解,应用一阶泰勒级数线性展开再次构造优化方程,最小化定位误差。此外,研究还推导得到基于协同定位的克劳美罗下界(Cooperative Localization-based Cramer-Rao Low Bound,CRLB-CL),以此作为评价标准评估提出的定位算法的有效性。仿真实验表明,在不同的条件下,ASM-RECL的定位精度较高于其他算法。