Search procedure for improving modified ambiguity function approach

摘要

The modified ambiguity function approach (MAFA) is a method of GNSS carrier phase data processing. In this method, the functional model of the adjustment problem contains the conditions ensuring the 'integemess' of the ambiguities. These conditions are expressed in the form of differentiable function. A prerequisite for obtaining the correct solution is a mechanism ensuring not only the 'integemess' of the ambiguities, but also appropriate convergence of the computational process. One of such mechanisms is a cascade adjustment, applying the linear combinations of the L1 and L2 signals with the integer coefficients and various wavelengths. Another method of increasing the efficiency of the MAFA method is based on the application of the integer decorrelation matrix to transform observation equations into equivalent, but better conditioned, observation equations. This paper presents the search procedure as the next technique of improving the MAFA method. This technique together with the decorrelation procedure allows to reduce the number of stages of the cascade adjustment and to obtain correct solution even in the case when a priori position is a few metres away from the actual position. In this paper an example of data processing using the proposed algorithm is given. The results of numerical tests based on real data are presented.