针对不同排序算法对模糊度解算存在降相关性能影响的问题，从理论上分析了自然升序法、对称旋转法及扰动升序法的降相关原理，并基于模拟数据和实测数据，从降相关时间、搜索时间、总体耗时、Bootstrapping成功率及条件数5个方面对3种算法进行对比分析。结果表明，降相关效率与搜索椭球压缩程度呈负相关关系，搜索椭球压缩程度越高，降相关效率越低；对于不同的排序算法，提高降相关性能的关键在于减少降相关时间及对条件方差按一定方向排序，进而提高搜索效率。"/>
Analysis of the Influence of Sorting on Decorrelation Performance in the Ambiguity Solution" />
To determine the influence of different sorting algorithms on the decorrelation performance of ambiguity in the ambiguity resolution, we theoretically analyze the natural ascending sorting method, the sorted QR decomposition method and the perturbed ascending sorting strategy. Secondly, based on simulated data and measured data, we compare and analyze the three algorithms in five aspects: decorrelation time, search time, overall time consumption, bootstrapping success rate, and condition number. The results show that decorrelation efficiency is negatively correlated with the degree of compression of the search ellipsoid. The higher the degree of compression of the search ellipsoid, the lower the decorrelation efficiency. For different sorting algorithms, the key to improve decorrelation performance is to reduce the decorrelation time and conditional variances are ordered in a certain direction to improve search efficiency."/>
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排序对模糊度解算中降相关性能的影响分析
Abstract：To determine the influence of different sorting algorithms on the decorrelation performance of ambiguity in the ambiguity resolution, we theoretically analyze the natural ascending sorting method, the sorted QR decomposition method and the perturbed ascending sorting strategy. Secondly, based on simulated data and measured data, we compare and analyze the three algorithms in five aspects: decorrelation time, search time, overall time consumption, bootstrapping success rate, and condition number. The results show that decorrelation efficiency is negatively correlated with the degree of compression of the search ellipsoid. The higher the degree of compression of the search ellipsoid, the lower the decorrelation efficiency. For different sorting algorithms, the key to improve decorrelation performance is to reduce the decorrelation time and conditional variances are ordered in a certain direction to improve search efficiency.
