Integer Ambiguity Search Technique Using Separated Gaussian Variables
Doyoon Kim , Jaegyu Jang, Changdon Kee
International Journal of Aeronautical and Space Sicences, vol. 5, no. 2, pp.1-8, 2004
Abstract : Real-Time Kinematic GPS positioning is widely used for many applications. Resolving ambiguities is the key to precise positioning. Integer ambiguity resolution is the process of resolving the unknown cycle ambiguities of double difference carrier phase data as integers. Two important issues of resolving are efficiency and reliability. In the conventional search techniques, we generally used chi -square random variables for decision variables. Mathematically, a chi-square random variable is the sum of mutually independent, squared zero-mean unit-variance normal (Gaussian) random variables. With this base knowledge, we can separate decision variables to several normal random variables. We showed it with related equations and conceptual diagrams. With this separation, we can improve the computational efficiency of the process without losing the needed performance. If. we average separated normal random variables sequentially, averaged values are also normal random variables. So we can use them as decision variables, which prevent from a sudden increase of some decision variable. With the method using averaged decision values, we can get the solution more quickly and more reliably.
To verify the performance of our proposed algorithm, we conducted simulations. We used some visual diagrams that are useful for intuitional approach. We analyzed the performance of the proposed algorithm and compared it to the conventional methods.
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