Analysis of accuracy estimation of own coordinates in the radio navigation systems with small bases between transmitters

Аuthors

Kishko D. V.

Moscow Aviation Institute (National Research University), 4, Volokolamskoe shosse, Moscow, А-80, GSP-3, 125993, Russia

e-mail: dvkishko@gmail.com

Abstract

One of the possible solutions of the determination position of aircrafts by using local ground-based high-precision radio navigation systems is considered in the article. This system consists of 4 evenly distributed on a circle of 50 meter radius ground-based transmitters, a control-correction station and an on-board receiver. The synchronization of signals is produced by operation of the control-correction station. Estimation of coordinates is performed on-board the aircraft.

Analysis of accuracy coordinates estimation when aircraft is far from the transmitters is shown in the paper. Characteristics of accuracy estimation of local coordinates are investigated for a few types of algorithms. The use of non-filtering Least-Squares Method (LSM), Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) is considered in the article.

The influence of divergence of the receiver’s clock has been examined on accuracy estimation for two types of measurements, i.e. range and difference pseudo ranges. In the first case, divergence of the receiver’s clock is included in state vector, while, in the second case, divergence is made up for forming of the difference pseudo ranges.

Results of simulation show the equal accuracy of LSM algorithms with pseudo ranges and different pseudo ranges. EKF and UKF with pseudo ranges measurements give more than twice better estimate in comparison with EKF and UKF with difference pseudo ranges measurements. This effect achieves because the influence of clock divergence in pseudo range methods include in the state vector. Results of simulation also show equal accuracy of EKF and UKF algorithms with the same measurements.

Keywords:

nonlinear filtration, coordinate estimation, local radio navigation systems, UKF, unscented kalman filter, EKF, extended Kalman filter

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