I.A. Nagin, A.Yu. Shatilov

It is widely known, that in heavy urban environment stable, precise navigation is difficult problem to solve. Urban canyons, multi-level roads and tunnels makes availability significantly suffer. However, this problem can be solved by using additional sensors, which provides information about user-s movement. By using such sensors and integration algorithms, one can efficiently increase navigation stability and precision. Some sensors, like ABS wheel speed sensors, provides enough information to make autonomous (reckoning) mode available. Development of proposed integration algorithm is aimed to satisfy GNSS users needs in heavy urban environment by integration GNSS receiver and ABS wheel speed sensors measurements. Algorithm was implemented by EKF with 8 state vector variables and estimates user coordinates. As input, it uses receiver coordinates and course measurements and wheel speed sensors velocity measurements. Also, integration algorithm capable of estimate wheel sensor errors and the automobile track width in case of GNSS receiver measurements availability. By compensating speed sensor errors, algorithm provides good precision in reckoning mode. Integration algorithm work has been modeled using real data. Data massive has been gathered while driving car in urban environment. Modeling showed, that integration algorithm reckoning mode precision is less than 5 percents of traveled distance, which is an excellent result for such systems.