The conventional direct position determination（DPD） algorithm processes all received signals on a single sensor.When sensors have limited computational capabilities or energy storage,it is desirable to distribute th...The conventional direct position determination（DPD） algorithm processes all received signals on a single sensor.When sensors have limited computational capabilities or energy storage,it is desirable to distribute the computation among other sensors.A distributed adaptive DPD（DADPD）algorithm based on diffusion framework is proposed for emitter localization.Unlike the corresponding centralized adaptive DPD（CADPD） algorithm,all but one sensor in the proposed algorithm participate in processing the received signals and estimating the common emitter position,respectively.The computational load and energy consumption on a single sensor in the CADPD algorithm is distributed among other computing sensors in a balanced manner.Exactly the same iterative localization algorithm is carried out in each computing sensor,respectively,and the algorithm in each computing sensor exhibits quite similar convergence behavior.The difference of the localization and tracking performance between the proposed distributed algorithm and the corresponding CADPD algorithm is negligible through simulation evaluations.展开更多
This paper focuses on the trusted vessel position acquisition using passive localization based on the booming low-earth-orbit(LEO) satellites. As the high signal-to-noise ratio(SNR) reception cannot always be guarante...This paper focuses on the trusted vessel position acquisition using passive localization based on the booming low-earth-orbit(LEO) satellites. As the high signal-to-noise ratio(SNR) reception cannot always be guaranteed at LEO satellites, the recently developed direct position determination(DPD)is adopted. For LEO satellite-based passive localization systems, an efficient DPD is challenging due to the excessive exhaustive search range leading from broad satellite coverage. In order to reduce the computational complexity, we propose a time difference of arrival-assisted DPD(TA-DPD) which minimizes the searching area by the time difference of arrival measurements and their variances. In this way, the size of the searching area is determined by both geometrical constraints and qualities of received signals, and signals with higher SNRs can be positioned more efficiently as their searching areas are generally smaller.Both two-dimensional and three-dimensional passive localization simulations using the proposed TA-DPD are provided to demonstrate its efficiency and validity. The superior accuracy performance of the proposed method, especially at low SNRs conditions, is also verified through the comparison to conventional two-step methods. Providing a larger margin in link budget for satellite-based vessel location acquisition,the TA-DPD can be a competitive candidate for trusted marine location service.展开更多
在网格直接定位方法的精度依赖于网格划分的精细程度,传统离网格方法缓解了对网格划分的依赖,但是仍然存在补偿精度低、算法复杂度过高的问题。针对这些问题,本文提出了一种参数字典动态更新的SOMP(Simultaneous Orthogonal Matching Pu...在网格直接定位方法的精度依赖于网格划分的精细程度,传统离网格方法缓解了对网格划分的依赖,但是仍然存在补偿精度低、算法复杂度过高的问题。针对这些问题,本文提出了一种参数字典动态更新的SOMP(Simultaneous Orthogonal Matching Pursuit)离网格直接定位方法。首先,利用子空间适应的方法对初始信号进行降噪处理,对二维空间进行粗网格的划分。其次,引入网格量化误差,不同于JSOMP(Joint Simultaneous Orthogonal Matching Pursuit)方法迭代后结算补偿值的方式,该方法在迭代的过程中使用泰勒补偿对每一次匹配相关度最高的网格点进行单源补偿,更新原有字典矩阵参数,从而得到较为理想的字典矩阵。仿真结果表明,本文所提算法能够有效克服网格失配的问题,得到精准的信源位置估计结果,相比于JSOMP、OG-SBI(Off-Grid Sparse Bayesian Inference)、MUSIC-Taylor(Multiple Signal Classification Based on Taylor Compensation)离网格方法,本文所提方法的运算速度更快、定位精度更高。展开更多
The localization of a stationary transmitter using moving receivers is considered. The original Direct Position Determination （DPD） methods, with combined Time Difference of Arrival （TDOA） and Frequency Difference...The localization of a stationary transmitter using moving receivers is considered. The original Direct Position Determination （DPD） methods, with combined Time Difference of Arrival （TDOA） and Frequency Difference of Arrival （FDOA）, do not perform well under low Signal-to-Noise Ratio （SNR）, and worse still, the computation cost is difficult to accept when the computational capabilities are limited. To get better positioning performance, we present a new DPD algorithm that proves to be more computationally efficient and more precise for weak signals than the conventional approach. The algorithm partitions the signal received with the same receiver into multiple non-overlapping short-time signal segments, and then uses the TDOA, the FDOA and the coherency among the short-time signals to locate the target. The fast maximum likelihood estimation, one iterative method based on particle filter, is designed to solve the problem of high computation load. A secondary but important result is a derivation of closed-form expressions of the Cramer-Rao Lower Bound （CRLB）. The simulation results show that the algorithm proposed in this paper outperforms the traditional DPD algorithms with more accurate results and higher computational efficiency, and especially at low SNR, it is more close to the CRLB.展开更多
To improve the resolution and accuracy of Direct Position Determination(DPD),this paper investigates the problem of positioning multiple emitters directly with a single moving Rotating Linear Array(RLA).Firstly,the ge...To improve the resolution and accuracy of Direct Position Determination(DPD),this paper investigates the problem of positioning multiple emitters directly with a single moving Rotating Linear Array(RLA).Firstly,the geometry of the RLA is formulated and analysed.According to its geometry,the intercepted noncoherent signals in multiple interception intervals are modeled.Correspondingly,the Multiple SIgnal Classification(MUSIC)based noncoherent DPD approach is proposed.Secondly,the synchronous coherent pulse signals are individually considered and formulated.And the coherent DPD approach which aims for localizing this special type of signal is presented by stacking all array responses at different interception intervals.Besides,we also derive the constrained Cramer-Rao Lower Bound(CRLB)expression for both noncoherent and coherent DPD with RLA under the constraint that the altitudes of the emitters are known.At last,computer simulations are included to examine the performance of the proposed approach.The results demonstrate that the localization accuracy and resolution of DPD with single moving linear array can be significantly improved by the array rotation.In addition,coherent DPD with RLA further improves the resolution and increases the maximum emitter number that can be localized compared with the noncoherent DPD with RLA.展开更多
基金supported by the National Natural Science Foundation of China(61101173)
文摘The conventional direct position determination（DPD） algorithm processes all received signals on a single sensor.When sensors have limited computational capabilities or energy storage,it is desirable to distribute the computation among other sensors.A distributed adaptive DPD（DADPD）algorithm based on diffusion framework is proposed for emitter localization.Unlike the corresponding centralized adaptive DPD（CADPD） algorithm,all but one sensor in the proposed algorithm participate in processing the received signals and estimating the common emitter position,respectively.The computational load and energy consumption on a single sensor in the CADPD algorithm is distributed among other computing sensors in a balanced manner.Exactly the same iterative localization algorithm is carried out in each computing sensor,respectively,and the algorithm in each computing sensor exhibits quite similar convergence behavior.The difference of the localization and tracking performance between the proposed distributed algorithm and the corresponding CADPD algorithm is negligible through simulation evaluations.
基金supported in part by the National Key Research and Development Program of China under Grant No. 2019YFB1803200the National Natural Science Foundation of China (NSFC) under Grant No. 61901020the Civil Aviation Administration of China。
文摘This paper focuses on the trusted vessel position acquisition using passive localization based on the booming low-earth-orbit(LEO) satellites. As the high signal-to-noise ratio(SNR) reception cannot always be guaranteed at LEO satellites, the recently developed direct position determination(DPD)is adopted. For LEO satellite-based passive localization systems, an efficient DPD is challenging due to the excessive exhaustive search range leading from broad satellite coverage. In order to reduce the computational complexity, we propose a time difference of arrival-assisted DPD(TA-DPD) which minimizes the searching area by the time difference of arrival measurements and their variances. In this way, the size of the searching area is determined by both geometrical constraints and qualities of received signals, and signals with higher SNRs can be positioned more efficiently as their searching areas are generally smaller.Both two-dimensional and three-dimensional passive localization simulations using the proposed TA-DPD are provided to demonstrate its efficiency and validity. The superior accuracy performance of the proposed method, especially at low SNRs conditions, is also verified through the comparison to conventional two-step methods. Providing a larger margin in link budget for satellite-based vessel location acquisition,the TA-DPD can be a competitive candidate for trusted marine location service.
文摘在网格直接定位方法的精度依赖于网格划分的精细程度,传统离网格方法缓解了对网格划分的依赖,但是仍然存在补偿精度低、算法复杂度过高的问题。针对这些问题,本文提出了一种参数字典动态更新的SOMP(Simultaneous Orthogonal Matching Pursuit)离网格直接定位方法。首先,利用子空间适应的方法对初始信号进行降噪处理,对二维空间进行粗网格的划分。其次,引入网格量化误差,不同于JSOMP(Joint Simultaneous Orthogonal Matching Pursuit)方法迭代后结算补偿值的方式,该方法在迭代的过程中使用泰勒补偿对每一次匹配相关度最高的网格点进行单源补偿,更新原有字典矩阵参数,从而得到较为理想的字典矩阵。仿真结果表明,本文所提算法能够有效克服网格失配的问题,得到精准的信源位置估计结果,相比于JSOMP、OG-SBI(Off-Grid Sparse Bayesian Inference)、MUSIC-Taylor(Multiple Signal Classification Based on Taylor Compensation)离网格方法,本文所提方法的运算速度更快、定位精度更高。
基金supported by the National Natural Science Foundation of China(No.61401513)
文摘The localization of a stationary transmitter using moving receivers is considered. The original Direct Position Determination （DPD） methods, with combined Time Difference of Arrival （TDOA） and Frequency Difference of Arrival （FDOA）, do not perform well under low Signal-to-Noise Ratio （SNR）, and worse still, the computation cost is difficult to accept when the computational capabilities are limited. To get better positioning performance, we present a new DPD algorithm that proves to be more computationally efficient and more precise for weak signals than the conventional approach. The algorithm partitions the signal received with the same receiver into multiple non-overlapping short-time signal segments, and then uses the TDOA, the FDOA and the coherency among the short-time signals to locate the target. The fast maximum likelihood estimation, one iterative method based on particle filter, is designed to solve the problem of high computation load. A secondary but important result is a derivation of closed-form expressions of the Cramer-Rao Lower Bound （CRLB）. The simulation results show that the algorithm proposed in this paper outperforms the traditional DPD algorithms with more accurate results and higher computational efficiency, and especially at low SNR, it is more close to the CRLB.
基金funded by the National Defence Science and Technology Project Fund of China(No.3101140)the Shanghai Aerospace Science and Technology Innovation Fund of China(No.SAST2015028)the Equipment Prophecy Fund of China(No.9140A21040115KG01001).
文摘To improve the resolution and accuracy of Direct Position Determination(DPD),this paper investigates the problem of positioning multiple emitters directly with a single moving Rotating Linear Array(RLA).Firstly,the geometry of the RLA is formulated and analysed.According to its geometry,the intercepted noncoherent signals in multiple interception intervals are modeled.Correspondingly,the Multiple SIgnal Classification(MUSIC)based noncoherent DPD approach is proposed.Secondly,the synchronous coherent pulse signals are individually considered and formulated.And the coherent DPD approach which aims for localizing this special type of signal is presented by stacking all array responses at different interception intervals.Besides,we also derive the constrained Cramer-Rao Lower Bound(CRLB)expression for both noncoherent and coherent DPD with RLA under the constraint that the altitudes of the emitters are known.At last,computer simulations are included to examine the performance of the proposed approach.The results demonstrate that the localization accuracy and resolution of DPD with single moving linear array can be significantly improved by the array rotation.In addition,coherent DPD with RLA further improves the resolution and increases the maximum emitter number that can be localized compared with the noncoherent DPD with RLA.
