Effective bias reduction methods for passive source localization using TDOA and GROA
10
Citation
19
Reference
10
Related Paper
Citation Trend
Keywords:
Cramér–Rao bound
FDOA
This paper explores the source localization problem using the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements when sensor location information suffers from random uncertainties. The analysis of the Cramér-Rao lower bound (CRLB) illustrates that the sensor uncertainties can considerably deteriorate the localization accuracy, so we fully incorporate the sensor location information uncertainties into the problem formulation. An iterative source localization algorithm is proposed to recursively solve the formulated problem, where the sensor information uncertainties is incorporated in each iteration to improve the localization performance.
FDOA
Cramér–Rao bound
Time of arrival
Cite
Citations (2)
This paper considers the problem of moving source localization by introducing an additional Doppler frequency shift (DFS) measurement into the previous location system using time differences of arrival (TDOAs) and frequency differences of arrival (FDOAs). Because of the separation of associated data channels and the difference in the estimation techniques, the DFS is independent of TDOA and FDOA measurements. The Cramer-Rao lower bound (CRLB) analysis shows that introducing DFS can improve source localization accuracy comparing with that of the TDOA and FDOA localization system, especially for the velocity location accuracy. An improved two-step weighted least-squares (I-TSWLS) source localization method utilizing DFS as well as TDOA and FDOA is developed. The solution is shown analytically to achieve the CRLB over small noise region, and have a better performance than that of the TSWLS method, especially when the sensor station error noises become large. Simulation results demonstrate the good performance of the proposed method.
FDOA
Cramér–Rao bound
Distributed File System
Carrier-to-noise ratio
Doppler frequency
Least-squares function approximation
Cite
Citations (9)
To solve the problem of time difference of arrival(TDOA) and frequency difference of arrival(FDOA) localization by fixed sensors,a new localization solution based on weighted least square and a tracking method based on extended Kalman filter are proposed.The geometric distribution of precision(GDOP) of localization Cramer-Rao lower bound(CRLB) is analyzed under the circumstances which some measurements errors exist in TDOA and FDOA parameters.The tracking performance of multiple-times measurements is simulated and is compared with performance using TDOA only.Simulation results show that adding FDOA information is useful to improve tracking precision of moving emitters.
FDOA
Cramér–Rao bound
Tracking (education)
Dilution of precision
Cite
Citations (1)
This paper is concerned with the problem of moving source localization using multiple-time time difference of arrival (TDOA) measurements collected by spatially distributed stationary receivers. We transform the nonlinear multiple-time TDOA equations into a set of pseudo-linear ones and then employ several weighted least-squares minimizations to obtain the source position and velocity estimates. The performance of the proposed solution is shown to be able to reach the Cramer-Rao lower bound (CRLB) accuracy by simulation studies when the TDOA measurement noises are sufficiently small.
Cramér–Rao bound
FDOA
Position (finance)
Time of arrival
Arrival time
Least-squares function approximation
Cite
Citations (6)
For optimal two-dimensional(2-D) sensors placement for 3-aircraft passive location system,a method based on maximum area principle is proposed.In this paper,3-aircraft time difference of arrival(TDOA) location,frequency difference of arrival(FDOA) location and hybrid TDOA/FDOA location are taken as examples.First,the basic description of passive location models is given.Then,the concept of effective location region is introduced based on Cramer-Rao Lower Bound(CRLB).Besides,the principle of maximum effective location area is given.Finally,the optimal 2-D sensors placement is investigated by computer simulation and the simulation results indicate some instructive conclusions,which reflect the characteristics of TDOA location system,FDOA localization system and hybrid TDOA/FDOA location system.
FDOA
Cramér–Rao bound
Direction finding
Cite
Citations (1)
Active target localization is one of the study emphases in wireless sensor network (WSN). When time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements are used to target localization, the measurements are nonlinearly related to the target location parameters. By the analysis of TDOA and FDOA linearized equations, when there exists sensor location error, active target localization using TDOA and FDOA measurements is a typical total least-squares (TLS) problem. The TLS solution for active target localization is presented in this paper. Its minimum square error ( MSE) is compared with Cramer-Rao lower bound (CRLB) through the simulation results.
FDOA
Cramér–Rao bound
Least-squares function approximation
Cite
Citations (32)
The aims of this work is to analyse the Cramer Rao lower bound (CRLB) for passive location of radio sources, as in multilateration (MLAT) systems and in their wide area version. The CRLB is used, in this paper, as the analysis method for the accuracy of position estimation using different measurements, related in a non-linear way to the target kinematics . The basic measurement is the classical TDOA (time difference of arrival used in hyperbolic location) with the possible addition of the differential Doppler shift or frequency difference of arrival (FDOA); other measurement such as angle of arrival or differential phase may be added to the proposed mathematical model.
FDOA
Cramér–Rao bound
Position (finance)
Angle of arrival
Geolocation
Time of arrival
Differential phase
Cite
Citations (19)
TDOA (time difference of arrival)와 FDOA (frequency difference of arrival)를 동시에 사용하는 신호원 위치추정 방법은 단일 정보를 이용하는 경우에 비해 높은 정확도를 가지며 이동 신호원의 속도 추정이 가능하다는 장점을 가지고 있다. 최근 종속 미지변수를 정의한 후 비반복적으로 해를 구하는 방법들이 제안되고 있으나 전자전 환경과 같이 수신단과 신호원 간의 거리가 상대적으로 먼 경우에는 추정 정확도가 낮고 모든 수신단 쌍이 동일한 기준 수신단을 공유하여야 한다는 운용상의 제약이 존재한다. 따라서 본 논문에서는 비선형 LS 최적해를 반복계산을 통해 얻어내는 Gauss-Newton 기법을 적용하여 이동신호원의 위치좌표와 속도벡터를 추정한다. 또한 이동 신호원의 위치와 속도 추정 결과를 효과적이고 정량적으로 분석하기 위해 CRLB (Cramer-Rao lower bound) 행렬을 각각의 부공간으로 분해하여 2차원 공간상에 독립된 CEP (circular error probable) 평면으로 도시한다. 모의실험을 통해 주어진 수신단 배치와 조합에서 이동 신호원의 위치 및 속도 추정 성능을 확인하고 분석 결과를 제시한다.
FDOA
Cramér–Rao bound
Cite
Citations (2)
Multi-station joint localization has important practical significance. In this paper, phase difference of arrival (PDOA) information is introduced into the joint time difference of arrival (TDOA) and frequency difference of arrival (FDOA) localization method to improve the target localization accuracy. First, the Cramer–Rao lower bound (CRLB) of the joint TDOA, FDOA and PDOA localization approach with multi-station precise phase synchronization is derived. Then, the CRLB of the joint TDOA, FDOA and differential PDOA (dPDOA) localization method for the case of phase asynchronization between observation stations is also presented. Furthermore, the authors analyze the influence of the phase wrapping problem on localization accuracy and propose solutions to solve the phase wrapping problem based on cost functions of grid search. Finally, iterative localization algorithms based on maximum likelihood (ML) are proposed for both TDOA/FDOA/PDOA and TDOA/FDOA/dPDOA scenarios, respectively. Simulation results demonstrate the localization performance of the proposed approaches.
FDOA
Cramér–Rao bound
Cite
Citations (8)
An effective method is presented for position tracking of a moving mobile terminal (MT). The method is based on time/distance difference of arrival (TDOA) estimation and Doppler measurements. TDOA locationing based on Chan's method provides an analytical solution which is closer to the Cramer-Rao Lower Bound (CRLB).However its accuracy is affected by multi-access interferences and non-line-of-sight (NLOS), thus making Doppler-aided positioning a good complementary technique due to its independency of the above effects. After acquiring the initial position of MT using TDOA information, the moving track is estimated by a hybrid method which combines TDOA with Doppler. Simulation results show this hybrid method can achieve better performance than TDOA or Doppler technique.
FDOA
Cramér–Rao bound
Non-line-of-sight propagation
Position (finance)
Tracking (education)
Cite
Citations (7)