Joint TDOA and AOA location algorithm

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.     

基于CAF相参积累的多载波信号时频差估计算法

多载波信号具有丰富的频域信息,相参积累能够拓宽信号的有效带宽,克服单载波信号带宽窄导致时差(time difference of arrival,TDOA)、频差(frequency difference of arrival,FDOA)参数估计精度不高的问题。以多载波信号的检测定位为背景,研究了基于多个载波信号互模糊函数(cross ambiguity function,CAF)相参积累的TDOA/FDOA参数估计算法,为多载波信号的无源定位提供高精度的定位参数估计方法。基于接收信号模型,推导了多载波信号的互模糊函数,从TDOA/FDOA两个维度分析了不同载波信号CAF的相位关系,通过相位补偿实现了多载波信号CAF的相参积累,并从理论上分析了TDOA/FDOA参数估计的性能改善情况。蒙特卡罗仿真表明,提出的多载波信号相参积累TDOA/FDOA估计算法性能明显优于单载波信号的估计性能,性能改善情况与理论分析一致。     

运动多站无源时差/频差联合定位方法

鉴于无源定位技术已经成为现代信息化作战的核心技术,提出了一种新的运动多站无源时差(time difference of arrival, TDOA)频差(frequency difference of arrival, FDOA)联合定位方法去解决无源定位系统中的非线性最优化问题。通过智能算法的启发,将优化后的基于线性递减权重和物竞天择的粒子群算法(particle swarm optimization algorithm based on linear decreasing weight and natural selection, WSPSO)与经典加权最小二乘算法(weighted least squares, WLS)相联合对目标进行跟踪定位。加权最小二乘定位算法在4个基站的情况下无法实现对辐射源的定位,所得定位结果会出现多解。而所提的运动多站联合定位算法在4个基站的条件下不存在初始目标位置估计和局部收敛等问题就能够实现辐射源的精确定位。通过大量仿真结果分析,本文所提的智能优化定位算法具有更高的目标定位精度和更稳健的定位性能,优于标准粒子群算法与优化PSO算法。     

跳频信号的相参与非相参积累时频差估计方法

跳频信号载频随时间变化发生跳变,因此跳频信号具有丰富的频域信息,而且其在时域上为连续信号,相比单跳信号也具有更丰富的时域信息.时频差估计精度与信号在时频域上的分布情况以及信号能量和噪声有关.时差估计主要与信号频域分布有关,而频差估计主要与信号时域分布有关.跳频信号时频域信息丰富,多跳相参积累后,时频差参数估计能够充分利...     

基于时差和频差的固定多站定位方法及分析

针对利用信号时差和频差信息的固定多站对运动辐射源定位问题,提出了一种基于加权最小二乘的单次定位解算新方法和基于扩展卡尔曼滤波的多次定位跟踪滤波方法。分析了存在时差和频差参数测量误差条件下的单次定位误差克拉美-罗下限几何分布图,并仿真了多次定位条件下的定位性能,将其与仅测时差定位的性能进行了比较。仿真表明,增加频差信息有助于提高对运动辐射源的定位跟踪精度。     

BFGS quasi-Newton location algorithm using TDOAs and GROAs

With the emergence of location-based applications in various fields,the higher accuracy of positioning is demanded.By utilizing the time differences of arrival(TDOAs) and gain ratios of arrival(GROAs),an efficient algorithm for estimating the position is proposed,which exploits the Broyden-Fletcher-Goldfarb-Shanno(BFGS) quasi-Newton method to solve nonlinear equations at the source location under the additive measurement error.Although the accuracy of two-step weighted-least-square(WLS) method based on TDOAs and GROAs is very high,this method has a high computational complexity.While the proposed approach can achieve the same accuracy and bias with the lower computational complexity when the signal-to-noise ratio(SNR) is high,especially it can achieve better accuracy and smaller bias at a lower SNR.The proposed algorithm can be applied to the actual environment due to its real-time property and good robust performance.Simulation results show that with a good initial guess to begin with,the proposed estimator converges to the true solution and achieves the Cramer-Rao lower bound(CRLB) accuracy for both near-field and far-field sources.     

Novel method for radial velocity difference estimation of moving targets with wideband signals

For the frequency difference of arrival （FDOA） esti-mation in passive location, this paper transforms the frequency difference estimation into the radial velocity difference estimation, which is difficult to achieve a high accuracy due to the mismatch between the sampling period and the pulse repetition interval. The proposed algorithm firstly estimates the point-in-time that each pulse arrives at two receivers accurately. Secondly two time of arrival （TOA） sequences are subtracted. And final y the radial ve-locity difference of a target relative to two stations with the least square method is estimated. This algorithm only needs accurate estimation of the time delay between pulses and is not influenced by parameters such as frequency and modulation mode. It avoids transmitting a large amount of data between two stations in real time. Simulation results corroborate that the performance is bet-ter than the arithmetic average of the Cramer-Rao lower bound （CRLB） for monopulse under suitable conditions.     

发射站/接收站位置误差下无源雷达DOA-TDOA目标定位算法

无源雷达中发射站和接收站位置误差的存在将显著降低目标定位精度。针对这一问题,将发射站和接收站位置误差考虑到基于波达方向和到达时差的无源雷达目标定位模型中,提出了一种目标位置代数解算法。首先,将波达方向和到达时差的测量方程线性化,考虑方程中的各项误差,采用加权最小二乘估计求解,并通过对加权矩阵的迭代更新,得到目标位置最优估计。推导了存在发射站和接收站位置误差条件下目标定位的克拉美罗下界,并从理论上证明了算法的定位精度可以达到克拉美罗下界。仿真结果表明,算法的定位精度优于现有算法,在发射站和接收站位置误差条件下定位精度仍能达到克拉美罗下界。     

发射站/接收站位置误差下无源雷达DOA-TDOA目标定位算法

无源雷达中发射站和接收站位置误差的存在将显著降低目标定位精度。针对这一问题,将发射站和接收站位置误差考虑到基于波达方向和到达时差的无源雷达目标定位模型中,提出了一种目标位置代数解算法。首先,将波达方向和到达时差的测量方程线性化,考虑方程中的各项误差,采用加权最小二乘估计求解,并通过对加权矩阵的迭代更新,得到目标位置最优估计。推导了存在发射站和接收站位置误差条件下目标定位的克拉美罗下界,并从理论上证明了算法的定位精度可以达到克拉美罗下界。仿真结果表明,算法的定位精度优于现有算法,在发射站和接收站位置误差条件下定位精度仍能达到克拉美罗下界。