Pseudo Randomized Search Strategy (prss*) of the Ambiguity Func1"ion Mapping

A technique has been developed for reliably resolving the GPS carrier phase ambiguity over a medium length baseline. A combination between three methods of optimization, global random search and ambiguity function mapping produced an efficient search algorithm what the author called the Pseudo Randomized Search Strategy (PRSS). The PRSS is a adaptive search technique that can learned high performance knowledge structures in reactive environments that provide information in the form of a objective function. What makes this search is efficient is that the objective function, where all the GPS measurement resides are evaluated periodically to guide the search to a global optimum. Numerical results shows that, in all the test cases, no more than 5% search of the total search space was conducted to determine the correct set of ambiguities. This result shows that the size of the search window does not play an important role in determining the efficiency of the search and therefore suitable for the on-the­ fly ambiguity resolution of a single frequen9Y CIA code receiver. 1.0 INTRODUCTION The Ambiguity Function Mapping (AFM) method was first introduced by Counselman and Gourevitch (1981) in their paper title Miniature Interferometer Terminals for Earth Surveying:Ambiguity and Multipath with the Global Positioning System. The roots of the AFM is believed to be from the VLBI techniques. Remondi (1984) was fIrst to use this method extensively for GPS static positioning and also for pseudo-kinematic positioning (Remondi, 1989). Mader (1990, 1992) also used the AFM for rapid static and kinematic GPS positioning. The most recent used of this method is by Han (1996) where some improvement on the computation time was gained particularly on the grid step size used. But beyond this, the AFM method never gained any ground. Theoretically, as proven by Lachapelle, Cannon and Erickson (1992), the AFM is equivalent to the Least Squares Search method which is widely used in other search techniques, such as, Fast Ambiguity Resolution Approach (Frei and Beutler, 1990), Cholesky Decomposition method (Landau and Euler, 1992), Least Squares Search (Hatch, 1990) and most recently the Least Squares Ambiguity Decorrelation Adjustment (Teunissen, 1994). Most of the above techniques has been incorporated in commercial GPS processing softwares. One of the main high point of the AFM compared to other technique is that it is immune to cycle slips. But still most researcher shy away from the AFM. In fact the AFM is the fust on-the-fly ambiguity resolution introduced. The main reason of the 'unpopularity' of the AFM is largely due to the