In Global navigation satellite system (GNSS) data processing, integer ambiguity acceptance\ntest is considered as a challenging problem. A number of ambiguity acceptance tests have been\nproposed from different perspective and then unified into the integer aperture estimation (IA)\nframework. Among all the IA estimators, the optimal integer aperture (OIA) achieves the highest\nsuccess rate with the fixed failure rate tolerance. However, the OIA is of less practical appealing due to\nits high computation complexity. On the other hand, the popular discrimination tests employ only two\ninteger candidates, which are the essential reason for their sub-optimality. In this study, a generalized\ndifference test (GDT) is proposed to exploit the benefit of including three or more integer candidates to\nimprove their performance from theoretical perspective. The simulation results indicate that the\nthird best integer candidates contribute to more than 70% success rate improvement for integer\nbootstrapping success rate higher than 0.8 case. Therefore, the GDT with three integer candidates\n(GDT3) achieves a good trade-off between the performance and computation burden. The threshold\nfunction is also applied for rapid determination of the fixed failure rate (FF)-threshold for GDT3.\nThe performance improvement of GDT3 is validated with real GNSS data set. The numerical results\nindicate that GDT3 achieves higher empirical success rate while the empirical failure rate remains\ncomparable. In a 20 km baseline test, the success rate GDT3 increase 7% with almost the same\nempirical failure rate.
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