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Research on high-precision passive localization based on phase difference changing rate

机译:基于相位差变化率的高精度无源定位研究

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摘要

Passive localization method has a wider applicable prospect as a rising localization resort with well flexibility. The acquisition of phase difference changing rate is a very practical problem in passive localization for theway how to get the phase difference, and a better error precision directly affects the accuracy of the localization. Firstly, based on the analysis of the positioning principle of phase difference changing rate, it studies the characteristics of phase difference changing rate and proposes a novel resolving phase ambiguity algorithm based on a double baselines system cosinetheorem(DBSCT),which caneliminate thephasedifference ambiguity efficiently.Secondly, it studies two typical methods to extract the high-precision phase difference changing rate from the unambiguity phase difference, namely, difference algorithm and Kalman algorithm. Finally, it compares the Kalman algorithm with the difference algorithm through computer simulation. Simulation results show that the Kalman algorithm can efficiently smoothen the phase difference data and suppress the measurement noise to achieve a high positioning accuracy. Simulation results also show that with a certain phase difference measurement accuracy, the phase difference rate accuracy extracted by the Kalman algorithm is higher than that we require. Therefore, we can appropriately relax the phase difference measurement accuracy requirements to achieve the same positioning accuracy. So, it has a great application value.
机译:被动定位方法作为一种新兴的具有良好灵活性的定位手段,具有广阔的应用前景。相位差变化率的获取是被动定位中如何获得相位差的一个非常实际的问题,更好的误差精度直接影响定位的准确性。首先,在分析相位差变化率的定位原理的基础上,研究了相位差变化率的特征,提出了一种基于双基线系统余弦定理(DBSCT)的分辨相位模糊度算法,可以有效地消除相位差模糊度。其次,研究了从无歧义相位差中提取高精度相位差变化率的两种典型方法,即差分算法和卡尔曼算法。最后,通过计算机仿真比较了卡尔曼算法和差分算法。仿真结果表明,卡尔曼算法可以有效地平滑相位差数据并抑制测量噪声,从而达到较高的定位精度。仿真结果还表明,在一定的相位差测量精度下,卡尔曼算法提取的相位差率精度高于我们要求的精度。因此,我们可以适当放宽对相位差测量精度的要求,以达到相同的定位精度。因此,它具有很大的应用价值。

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