Ambiguity of whole cycle rapid obtaining method based on real-coding adaptive genetic algorithm

Abstract

The invention discloses an ambiguity of whole cycle rapid obtaining method based on a real-coding adaptive genetic algorithm. The method includes the following steps: S1, observing data through a carrier wave phase, and establishing a carrier wave phase double difference observation equation; S2, after linearization of the observation equation, utilizing Kalman filtering to obtain a floating pointsolution of ambiguity of a whole cycle and a corresponding covariance matrix; S3, taking a known baseline length as a constraint condition and determining the search range of the ambiguity of the whole cycle; S4, performing decorrelation on the floating point solution and the covariance matrix through an improved Cholesky decomposition method; and S5, determining a fitness function on the basis of a target function, determining all running parameters in an IAGA, conducting real coding on a problem, and finally searching an optimal solution of the ambiguity of the whole cycle through the IAGA.Corresponding crossover and mutation probabilities can be adjusted in a non-linear manner on the basis of individual fitness, a Hamming cliff problem can be solved by means of real coding, and the solving efficiency of the ambiguity of the whole cycle can be increased.

Description

Technical field [0001] The invention relates to the technical field of solving the carrier phase integer ambiguity by using an optimization algorithm, in particular to a method for quickly acquiring the integer ambiguity based on a real-coded adaptive genetic algorithm. Background technique [0002] With the development of satellite navigation technology, applications in various fields around the world not only rely on it more and more, but also have higher requirements for positioning accuracy and timeliness. Since the original observation value of the satellite carrier phase contains the whole-cycle ambiguity, the distance between the satellite and the receiver determined directly by the observation value is not equal to the true distance. However, once the ambiguity of the whole week is accurately calculated, the distance between the satellite and the receiver can be obtained with cm or even mm-level accuracy, so that cm or even mm-level positioning can be performed. Therefor...

AI Technical Summary

Problems solved by technology

Since the running parameters of the simple genetic algorithm, the crossover probability and mutation probability are constant, it is easy to make the initial crossover probability and mutation probability unable to meet the search at the initial and later stages of the operation, which affects the speed and efficiency of the search

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