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The angle-of-arrival integrity monitoring efficiency under multiple observations


A.P. Melikhova – Part-programming engineer, LLC «Special Technology Center» (SPb). E-mail: I.A. Tsikin – Dr. Sc. (Eng.), Professor, Peter The Great St.Petersburg Polytechnic University. E-mail:

Mostly known interferences to global navigation satellite systems are ionosphere and tropospheric influences, ephemeris data and selective availability errors, satellite onboard and user receiver clock errors, differential corrections errors and the interferences caused by false navigation signal source impact. Particular attention must be paid to the intentional interference caused by the false navigation signal source impact. In case when power of false signal is greater than the power of the authentic signal user calculate incorrect information about its position. As a result of such a failure the measured position of a user can significantly deviate from its true values. A case when this error value exceeds an admissible limit can be referred to as a navigation system integrity failure, and a procedure to detect such a failure is known as integrity monitoring. The paper considers the navigation integrity monitoring method which is based on the multiple observations of the measured and calculated navigation signal source angle-of-arrival parameters. The decision-making procedure of integrity presence or absence is performed on the basis of a separate analysis of multidimensional samples for each of the direction-finding parameters (azimuth and elevation) followed by logical addition of the decisions. The decision-making algorithm is based on the maximum likelihood method with decision threshold for Neumann–Pearson criterion. This is considered a static model of the direction-finding parameters behavior when the measured parameters variances are much larger than the calculated ones, which is typical for antennas with a small number of elements. The main probability-based integrity monitoring characteristics for this algorithm were obtained, and the areas where the algorithm is effective are analyzed. The advantage of multiple observations method over the single one is estimated .


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