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中文摘要：
为了提高干扰情况下目标的定位精度,提出一种基于数据质量分析的地面固定被动传感器组网变门限聚类定位算法。该算法充分利用传感器组网和数据质量分析的优点,首先将各传感器量测转换为目标的估计位置点,并按照距离平方和的方法对各位置点进行数据质量分析;其次构造检验统计量,根据位置点数量的变化自适应调整聚类门限进而对位置点中心进行数据质量分析;最后根据分析结果确定高质量位置点类别并获得目标的估计位置。通过和最小均方误差估计算法（MMSE）相比较,变门限聚类定位算法可有效消除低质量数据对定位结果的影响,从而提高了目标的定位精度。仿真结果验证了从数据质量分析的角度对目标进行组网定位的有效性。
英文摘要：
With the help of a sensor network which is fixed on the ground,a clustering localization algorithm with adaptive threshold based on Data Quality（DQ） analyzing is presented in order to enhance localization precision in a jamming scenario.Taking full advantage of sensor network and DQ analysis,estimated positions of target can be obtained from sensors＇ measurements firstly,and the DQ of each position is scaled according to the Distance Square Sum method.Secondly,a testing statistics is constructed from which the DQ of certain estimated positions＇ center is scaled by means of adjusting the clustering threshold adaptively,and the threshold is relative with the number of estimated positions.Finally,the sort of high quality positions is confirmed and the target position can be obtained.By eliminating the possible influence produced by low quality data,the presented algorithm can improve localization precision effectively in comparison with the MMSE algorithm.Simulation results verify the clustering localization algorithm based on DQ analysis presented in this paper.
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