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A Novel Interpolation Method for TDOA and FDOA Estimation based on Second-order Cone Programming

机译:基于二阶锥规划的TDOA和FDOA估计的新插值方法

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Locating an emitting source based on time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements from passive sensors has widely been used in radar and sensor networks. The localization accuracy is directly influenced by the TDOA and FDOA estimation accuracy. While considerable research works have been performed on algorithm development, limited accuracy has been paid in TDOA and FDOA estimation. Therefore, a novel joint TDOA and FDOA estimation interpolation method with sub-sample accuracy based on second-order cone programming (SOCP) is presented in this paper. It combines the advantages of “soft” constraint and “hard” constraint to build optimization models, and obtains the interpolation surface through the SOCP, which can change the discrete ambiguity surface into continuous surface. The estimation accuracy of TDOA and FDOA is no longer forced to lie on sampling interval and sampling time. Simulation results indicate that the proposed method is effective and outperforms the other traditional interpolation algorithms regarding the estimation accuracy.
机译:基于来自无源传感器的到达时间差(TDOA)和到达频率差(FDOA)测量来定位发射源已广泛用于雷达和传感器网络中。定位精度直接受TDOA和FDOA估计精度的影响。尽管已经在算法开发方面进行了大量研究工作,但在TDOA和FDOA估计中却付出了有限的准确性。因此,本文提出了一种基于二阶锥规划(SOCP)的具有子样本精度的联合TDOA和FDOA估计插值方法。它结合了“软”约束和“硬”约束的优点,建立了优化模型,并通过SOCP获得了插值曲面,从而可以将离散的模糊曲面变为连续曲面。 TDOA和FDOA的估计精度不再受制于采样间隔和采样时间。仿真结果表明,该方法是有效的,并且在估计精度方面优于其他传统插值算法。

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