Abstract Modern global navigation satellite systems introduce additional frequencies that benefit the performance of cycle-slip detection and repair. However, recent related studies have focused on the success rate (SR) of cycle-slip detection rather than that of repair. This study considered common combinations of triple-frequency observations and analyzed their advantages/disadvantages in detail. To detect and repair cycle slip, combinations of the two main forms of observation were constructed based on the classic least-squares ambiguity decorrelation adjustment (LAMBDA) method, with consideration of residual ionospheric variations. A large volume of simulation data was used to test the cycle-slip repair SR of different combinations of observations under different ionospheric conditions. Theoretical and experimental results showed that using different forms of two geometry-free (GF) phase or two extra-wide-lane (EWL) combinations to fix the cycle-slip solution using the LAMBDA method was irrelevant to the cycle-slip repair SR of the 1EWL & 2GF and 2EWL & 1GF phase combination forms, respectively. Under the same ionospheric conditions, the performance of 2EWL & 1GF phase combinations was significantly better than that of 1EWL & 2GF phase combinations in terms of cycle-slip repair SR. The difference was mainly reflected in the performance of cycle-slip detection. The larger the maximum threshold of ionospheric variation (MTIV) value of GF phase combination observations, which represents the ability to resist the insensitive cycle-slip group ±(1, 1, 1), the lower the cycle-slip repair SR for those combinations. Therefore, the optimal strategy would be to employ strong GF phase combinations with a large MTIV value to detect cycle slip, and to employ excellent GF phase combinations with a high SR to repair cycle slip.
Effect of selection of combined observations on cycle-slip repair success rate for BDS triple-frequency signals
Advances in Space Research ; 66 , 12 ; 2914-2925
2020-03-10
12 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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