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TOA-based joint synchronization and source localization with random errors in sensor positions and sensor clock biases

机译:基于TOA的联合同步和源定位,传感器位置和传感器时钟偏差随机误差

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This paper considers the problem of joint synchronization and source localization using time of arrival (TOA) when the known sensor positions and sensor clock biases are subject to random errors. We derive the Cramer-Rao lower bound (CRLB) of the source position and the source clock bias, and quantify the amount of estimation performance degradation due to sensor position errors and sensor clock bias errors. A mean square error (MSE) analysis is conducted and it shows that ignoring the errors in the known sensor positions and sensor clock biases would lead to an estimation accuracy worse than the CRLB. This paper then proceeds to develop a new joint synchronization and source localization algorithm. The new method takes into consideration the presence of sensor position errors and sensor clock bias errors, and has the advantage of being a closed-form solution. Theoretical performance analysis proves that the proposed algorithm can attain the CRLB accuracy under small noise condition. Computer simulations are used to corroborate the theoretical derivations and demonstrate the good performance of the newly developed algorithm.
机译:当已知的传感器位置和传感器时钟偏置受到随机误差的影响时,本文考虑使用到达时间(TOA)进行联合同步和源定位的问题。我们推导了源位置和源时钟偏置的Cramer-Rao下界(CRLB),并量化了由于传感器位置误差和传感器时钟偏置误差而导致的估计性能下降量。进行了均方误差(MSE)分析,结果表明,忽略已知传感器位置和传感器时钟偏差中的误差会导致估计精度比CRLB差。然后,本文着手开发一种新的联合同步和源定位算法。新方法考虑了传感器位置误差和传感器时钟偏置误差的存在,并具有封闭形式的优点。理论性能分析表明,该算法在小噪声条件下可以达到CRLB精度。计算机仿真用于证实理论推导,并证明了新开发算法的良好性能。

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