基于约束加权最小二乘的时差频差联合定位算法

针对运动目标源定位问题，提出了一种基于约束加权最小二乘(Constrained Weighted Leas t-Squares, CWLS)的时差频差定位算法。该算法利用目标源到达多个接收站的时差和频 差信息，对目标源的位置和速度进行估计。通过引入中间变量，将时差频差非线性方程转换 成伪线性方程(中间变量与目标源位置和速度之间存在约束关系)，再对此约束条件引入拉格 朗日乘子技术，将此伪线性方程的求解转化为求条件极值问题，创造性地求解了此非线性定 位方程，提高了定位精度，并能满足实时性和全局收敛要求。仿真实验表明，该算法在保持 相近复杂度的同时，进一步提高了定位性能，优于两步加权最小二乘算法，在噪声较高时仍 然能达到克拉美罗下限。

Constrained weighted least-squares algorithm for moving source location using TDOA and FDOA measurements

By utilizing the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements of a signal received at a nu mber of receivers, a constrained weighted least-squares (CWLS) algorithms for e stimating the position and velocity of a moving source is proposed. By utilizing the Lagrange multipliers technique, the known relation between the intermediate variables and the source location coordinates can be exploited to constrain th e solution. And, on basis of convolute and polynomial rooting operations, the La grange multipliers can be obtained efficiently and robustly, which can allow rea l-time implementation as well as ensure global convergence. Simulation results show that the proposed estimator achieves remarkably better performance than the two-step weighted least squares(WLS) approach especially for higher measuremen t noise level, which makes the Cramér-Rao lower bound(CRLB) at a sufficiently h igh noise level before the threshold effect occurs possible.