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

机译:基于二阶锥形编程的TDOA和FDOA估计的一种新型插值方法

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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:基于到达时间差(TDOA)的发射源(TDOA)和到达的频率差(FDOA)来自无源传感器的测量,广泛用于雷达和传感器网络。本地化精度直接受TDOA和FDOA估计准确性的影响。虽然在算法开发上进行了相当大的研究作品,但TDOA和FDOA估计已经支付了有限的准确性。因此,本文介绍了基于二阶锥编程(SOCP)的具有子样本精度的新型联合TDOA和FDOA估计插值方法。它结合了“软”约束和“硬”约束来构建优化模型的优点,并通过SOCP获得插值表面,这可以将离散的模糊表面改变为连续表面。 TDOA和FDOA的估计准确性不再被迫避开采样间隔和采样时间。仿真结果表明,所提出的方法是有效和优于关于估计精度的其他传统插值算法。

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