This paper investigates the problem of target position estimation with a single-observer passive coherent location（PCL） system. An approach that combines angle with time difference of arrival（ATDOA） is used to est...This paper investigates the problem of target position estimation with a single-observer passive coherent location（PCL） system. An approach that combines angle with time difference of arrival（ATDOA） is used to estimate the location of a target. Compared with the TDOA-only method which needs two steps, the proposed method estimates the target position more directly. The constrained total least squares（CTLS） technique is applied in this approach. It achieves the Cramer–Rao lower bound（CRLB） when the parameter measurements are subject to small Gaussian-distributed errors. Performance analysis and the CRLB of this approach are also studied. Theory verifies that the ATDOA method gets a lower CRLB than the TDOA-only method with the same TDOA measuring error. It can also be seen that the position of the target affects estimating precision.At the same time, the locations of transmitters affect the precision and its gradient direction.Compared with the TDOA, the ATDOA method can obtain more precise target position estimation.Furthermore, the proposed method accomplishes target position estimation with a single transmitter,while the TDOA-only method needs at least four transmitters to get the target position. Furthermore,the transmitters＇ position errors also affect precision of estimation regularly.展开更多
Considering the estimation accuracy reduction of Frequency Difference of Arrival （FDOA） caused by relative Doppler companding, a joint Time Difference of Arrival （TDOA）, FDOA and differential Doppler rate estimati...Considering the estimation accuracy reduction of Frequency Difference of Arrival （FDOA） caused by relative Doppler companding, a joint Time Difference of Arrival （TDOA）, FDOA and differential Doppler rate estimation method is proposed and its Cramer-Rao low bound is derived in this paper. Firstly, second-order ambiguity function is utilized to reduce the dimensionality and estimate initial TDOA and differential Doppler rate. Secondly, the TDOA estimation is updated and FDOA is obtained using cross ambiguity function, in which relative Doppler com- panding is compensated by the existing differential Doppler rate. Thirdly, differential Doppler rate estimation is updated using cross estimator. Theoretical analysis on estimation variance and Cramer-Rao low bound shows that the final estimation of TDOA, FDOA and differential Doppler rate performs well at both low and high signal-noise ratio, although the initial estimation accuracy of TDOA and differential Doppler rate is relatively poor under low signal-noise ratio conditions. Simulation results finally verify the theoretical analysis and show that the proposed method can overcome relative Doppler companding problem and performs well for all TDOA, FDOA and differential Doppler rate estimation.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
For the influence caused by multipath fading and non-line-of-sight(NLOS)transmission,it is challenging to accurately localize a moving signal source in complex environment by using the wireless sensor network(WSN)on t...For the influence caused by multipath fading and non-line-of-sight(NLOS)transmission,it is challenging to accurately localize a moving signal source in complex environment by using the wireless sensor network(WSN)on the ground.In this paper,we establish a special WSN in the sky to address this challenge,where each sensor is loaded on an unmanned aerial vehicle(UAV)and the operation center of all the UAVs is fixed on the ground.Based on the analyzing of the optimal distribution and the position error calibration of all the sensors,we formulate the localization scheme to estimate the position of the target source,which combines the time difference of arrival(TDOA)method and the frequency difference of arrival(FDOA)method.Then by employing the semidefinite programming approach,we accurately obtain the position and velocity of the signal source.In the simulation,the validity of the proposed method is verified through the performance comparison.展开更多
基金supported by the National High Technology Research and Development Program of China(863 Program)(No.2012AA7031015)
文摘This paper investigates the problem of target position estimation with a single-observer passive coherent location（PCL） system. An approach that combines angle with time difference of arrival（ATDOA） is used to estimate the location of a target. Compared with the TDOA-only method which needs two steps, the proposed method estimates the target position more directly. The constrained total least squares（CTLS） technique is applied in this approach. It achieves the Cramer–Rao lower bound（CRLB） when the parameter measurements are subject to small Gaussian-distributed errors. Performance analysis and the CRLB of this approach are also studied. Theory verifies that the ATDOA method gets a lower CRLB than the TDOA-only method with the same TDOA measuring error. It can also be seen that the position of the target affects estimating precision.At the same time, the locations of transmitters affect the precision and its gradient direction.Compared with the TDOA, the ATDOA method can obtain more precise target position estimation.Furthermore, the proposed method accomplishes target position estimation with a single transmitter,while the TDOA-only method needs at least four transmitters to get the target position. Furthermore,the transmitters＇ position errors also affect precision of estimation regularly.
基金supported by the National Natural Science Foundation of China(No.61671273)
文摘Considering the estimation accuracy reduction of Frequency Difference of Arrival （FDOA） caused by relative Doppler companding, a joint Time Difference of Arrival （TDOA）, FDOA and differential Doppler rate estimation method is proposed and its Cramer-Rao low bound is derived in this paper. Firstly, second-order ambiguity function is utilized to reduce the dimensionality and estimate initial TDOA and differential Doppler rate. Secondly, the TDOA estimation is updated and FDOA is obtained using cross ambiguity function, in which relative Doppler com- panding is compensated by the existing differential Doppler rate. Thirdly, differential Doppler rate estimation is updated using cross estimator. Theoretical analysis on estimation variance and Cramer-Rao low bound shows that the final estimation of TDOA, FDOA and differential Doppler rate performs well at both low and high signal-noise ratio, although the initial estimation accuracy of TDOA and differential Doppler rate is relatively poor under low signal-noise ratio conditions. Simulation results finally verify the theoretical analysis and show that the proposed method can overcome relative Doppler companding problem and performs well for all TDOA, FDOA and differential Doppler rate estimation.
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supported by The Science and Technology Innovation Team Plan of Shaanxi Province (2017-KCT-30-02)The Key Research and Development Program of Shaanxi Province (2018GY-150)+1 种基金The Foundation Research Project of Shaanxi Province (The Natural Science Fund. 2018JQ6093)The Science and Technology Plan Project of Xi’an City (201805040YD18CG24-3)
文摘For the influence caused by multipath fading and non-line-of-sight(NLOS)transmission,it is challenging to accurately localize a moving signal source in complex environment by using the wireless sensor network(WSN)on the ground.In this paper,we establish a special WSN in the sky to address this challenge,where each sensor is loaded on an unmanned aerial vehicle(UAV)and the operation center of all the UAVs is fixed on the ground.Based on the analyzing of the optimal distribution and the position error calibration of all the sensors,we formulate the localization scheme to estimate the position of the target source,which combines the time difference of arrival(TDOA)method and the frequency difference of arrival(FDOA)method.Then by employing the semidefinite programming approach,we accurately obtain the position and velocity of the signal source.In the simulation,the validity of the proposed method is verified through the performance comparison.
