基于稀疏重构的TOA定位估计算法

目标在定位空间中具有稀疏特性,基于该特点提出了一种稀疏重构的时延定位算法;已有的来波到达时间(time-of-arrival, TOA)算法大部分只利用了单次TOA进行估计,其定位结果受噪声影响较大,因此进一步提出对多样本的到达时间进行联合估计,从而提高算法对噪声的稳健性,并提高算法的定位精度。与已有算法相比,所提算法的优点是定位精度更高,对噪声有更强的稳健性。仿真结果验证了所提算法的有效性。

Time-of-arrival positioning estimation algorithm based on sparse reconstruction

Based on the feature that the targets are sparse in space, a positioning algorithm based on sparse reconstruction is proposed. Most of the existing time-of-arrival (TOA) algorithms use only one sample to estimate targets and they are sensitive to noise. The multi sample joint estimation algorithm is further proposed to improve the noise robustness and the positioning accuracy of the algorithm. Compared with the existing algorithms, the proposed algorithm has a higher positioning accuracy and stronger noise robustness. Simulation results demonstrate the effectiveness of the proposed algorithm.