Modified Kalman Filter for GPS Position Estimation over the Indian Sub Continent

Position accuracy is the measure of a system's capability to provide quality estimates, which in turn depends mainly on measurement noise and the type of algorithm employed. Though many positioning algorithms have emerged, due to its exceptional performance in a wide range of real time applications, the Kalman Filter Estimator (KFE) is used often for their implementation. So this paper concentrates in improving its accuracy further while introducing a new observation matrix in its estimation process and succeeds in performing the same. This paper also extends the modified algorithm for GPS receiver position estimation over the Indian subcontinent. Real time data collected from GPS receiver located at IISC, Bangalore (Lat/Lon: 13.01(0)N /77.56(0)E), India is used to evaluate the performance of this developed algorithm called Modified Kalman Filter Estimator (MKFE). GPS Statistical Accuracy Measures (SAM) such as Circular Error Probability (CEP), Spherical Error Probability (SEP) etc. are used for performance evaluation. From the results it is observed that the proposed MKFE has faster convergence rate with high accuracy and is suitable for real time defence applications over the Indian subcontinent. (C) 2016 The Authors. Published by Elsevier B.V.