To solve the problem of multiple moving sources passive location, a novel blind source separa- tion （BSS） algorithm based on the muhiset canonical correlation analysis （MCCA） is presented by exploiting the differe...To solve the problem of multiple moving sources passive location, a novel blind source separa- tion （BSS） algorithm based on the muhiset canonical correlation analysis （MCCA） is presented by exploiting the different temporal structure of uncorrelated source signals first, and then on the basis of this algorithm, a novel multiple moving sources passive location method is proposed using time difference of arrival （TDOA） and frequency difference of arrival （FDOA） measurements. The key technique of this location method is TDOA and FDOA joint estimation, which is based on BSS. By blindly separating mixed signals from multiple moving sources, the multiple sources location problem can be translated to each source location in turn, and the effect of interference and noise can also he removed. The simulation results illustrate that the performance of the MCCA algorithm is very good with relatively light computation burden, and the location algorithm is relatively simple and effective.展开更多
For the joint time difference of arrival（TDOA） and angle of arrival（AOA） location scene,two methods are proposed based on the rectangular coordinates and the polar coordinates,respectively.The problem is solved pe...For the joint time difference of arrival（TDOA） and angle of arrival（AOA） location scene,two methods are proposed based on the rectangular coordinates and the polar coordinates,respectively.The problem is solved perfectly by calculating the target position with the joint TDOA and AOA location.On the condition of rectangular coordinates,first of all,it figures out the radial range between target and reference stations,then calculates the location of the target.In the case of polar coordinates,first of all,it figures out the azimuth between target and reference stations,then figures out the radial range between target and reference stations,finally obtains the location of the target.Simultaneously,simulation analyses show that the theoretical analysis is correct,and the proposed methods also provide the application of the joint TDOA and AOA location algorithm with the theoretical basis.展开更多
定位精度是评价雷电定位网络的重要指标之一,定位算法直接关系到雷电探测结果的精度。经典定位法抗误差干扰能力差、定位精度低,传统迭代算法易于发散且会陷入局部最优。为了实现更有效的定位,在定位计算中引入改进密度聚类算法(adaptiv...定位精度是评价雷电定位网络的重要指标之一,定位算法直接关系到雷电探测结果的精度。经典定位法抗误差干扰能力差、定位精度低,传统迭代算法易于发散且会陷入局部最优。为了实现更有效的定位,在定位计算中引入改进密度聚类算法(adaptive density-based spatial clustering of applications with noise,ADBSCAN)。通过雷击事故实例和区域仿真分析了定位算法的性能。结果表明,ADBSCAN不需要人工干预,对于雷电定位结果的聚类效果更好;基于ADBSCAN的雷电定位算法克服了传统定位算法的缺点,提高了抗误差干扰的能力,能稳定并精确求解出雷击点。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
基金Supported by the National High Technology Research and Development Program of China(No.2009AAJ116,2009AAJ208,2010AA7010422)the National Science Foundation for Post-Doctoral Scientists of China(No.20080431379,200902671)the Hubei Natural Science Foundation(No.2009CDB031)
文摘To solve the problem of multiple moving sources passive location, a novel blind source separa- tion （BSS） algorithm based on the muhiset canonical correlation analysis （MCCA） is presented by exploiting the different temporal structure of uncorrelated source signals first, and then on the basis of this algorithm, a novel multiple moving sources passive location method is proposed using time difference of arrival （TDOA） and frequency difference of arrival （FDOA） measurements. The key technique of this location method is TDOA and FDOA joint estimation, which is based on BSS. By blindly separating mixed signals from multiple moving sources, the multiple sources location problem can be translated to each source location in turn, and the effect of interference and noise can also he removed. The simulation results illustrate that the performance of the MCCA algorithm is very good with relatively light computation burden, and the location algorithm is relatively simple and effective.
基金supported by the National Natural Science Foundation of China(6107210761271300)+4 种基金the Shaanxi Industry Surmount Foundation(2012K06-12)the Arm and Equipment Pre-research Foundationthe Fundamental Research Funds for the Central Universities of China(K0551302006K5051202045K50511020024)
文摘For the joint time difference of arrival（TDOA） and angle of arrival（AOA） location scene,two methods are proposed based on the rectangular coordinates and the polar coordinates,respectively.The problem is solved perfectly by calculating the target position with the joint TDOA and AOA location.On the condition of rectangular coordinates,first of all,it figures out the radial range between target and reference stations,then calculates the location of the target.In the case of polar coordinates,first of all,it figures out the azimuth between target and reference stations,then figures out the radial range between target and reference stations,finally obtains the location of the target.Simultaneously,simulation analyses show that the theoretical analysis is correct,and the proposed methods also provide the application of the joint TDOA and AOA location algorithm with the theoretical basis.
文摘定位精度是评价雷电定位网络的重要指标之一,定位算法直接关系到雷电探测结果的精度。经典定位法抗误差干扰能力差、定位精度低,传统迭代算法易于发散且会陷入局部最优。为了实现更有效的定位,在定位计算中引入改进密度聚类算法(adaptive density-based spatial clustering of applications with noise,ADBSCAN)。通过雷击事故实例和区域仿真分析了定位算法的性能。结果表明,ADBSCAN不需要人工干预,对于雷电定位结果的聚类效果更好;基于ADBSCAN的雷电定位算法克服了传统定位算法的缺点,提高了抗误差干扰的能力,能稳定并精确求解出雷击点。
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.
