Sviridenko Vladimir

Director of Engineering

Vladimir A.Sviridenko is a Doctor of science (technology), professor, Director of Engineering of Group of companies SPIRIT DSP. He is a specialist in development of radio engineering and telecom systems, processing of speech and video information, digital signal processing etc. Also he is an author and co-author of 200+ publications (monographs, books, brochures, articles, papers on conferences, lectures) and 40+ patents. About 20 years ago he organized updated R&D center in SPIRIT company which is engaged in research and development different systems and software solutions for different telecom and navigation applications, videoconferencing, speech technologies, image and video processing, computer vision, most of them were licensed by differ world companies from different countries (including USA, Europe, Israel, Japan, S.Korea, China etc (250 and more companies). Software developed by SPIRIT was romed in chips of such knows vendors as TI, STM,CML Microcircuit, DSPG. Also SPIRIT made its contribution in advanced navigation solutions including GG-receiver with interference suppression, the first all chip based Glonass/GPS-receiver, supersensitive software receiver SSSR, innovative solutions on indoor-positioning of moving objects which were financed by Skolkovo Fund (space cluster) etc.


In-Vehicle Navigation Solutions
“Car-navigation in GNSS-signals blocking conditions based mobile platform ”
Accent in the report was done on car-navigation in complex urban environment (with accuracy 3m) when signal blocking conditions are appeared (for example, in tunnels) and solution of indoor-positioning problem (with accuracy 1-2m) for cars. In the first case outdoor positioning is based on known approach to integration INS+GNSS, Kalman Filter and correction navigation data at line of sight satellites with possible support from an odometer. Effectiveness of the solution is illustrated by trajectories on car passage in tunnels of Moscow and Shanghai. And a task on indoor positioning was based on data fusion method which was realized with usage Particle Filter. In the second case it is based on a method of kinematic parameters estimation (in particular, estimation of velocity/acceleration vectors) and next their usage according to Dead Reckoning technology as alternatively approach. The result for the second case is presented on YouTube (see which demonstrates general quality of the solution of the task on outdoor+indoor car positioning at its movement in urban environment, after that a movement in a garage under rough (with known lay-out (a map) and map matching support) and after that next departure to a street. It is reasonable to note that sensor base, hardware support and operating environment for such software solution are set by hand-picked smartphone but it is enough prevalent case. So a porting of the navigation solution on differ platforms including embedded car board computer is no difficult task.