Professor Washington Yotto Ochieng is the Head of the Centre for Transport Studies and Chair of Positioning and Navigation Systems in the Department of Civil and Environmental Engineering at Imperial College London. He is also the Director of the Imperial College Engineering Geomatics Group (ICEGG).
After gaining a PhD in Space Geodesy at the University of Nottingham, Prof. Ochieng worked there as a Research Associate before moving to Racal Electronics (Thales) as Principal Engineer (Navigation specialist) where he participated in various international industrial consortia developing satellite navigation systems and products. He moved to Imperial College London in 1997.
Professor Ochieng's research interests are in the design of positioning and navigation systems for land, sea and air applications; Air Traffic Management (ATM) and Intelligent Transport Systems (ITS). He has made significant contributions to major international projects including the design of the European Geostationary Navigation Overlay Service (EGNOS) and GALILEO, GNSS measurement error modelling, specification of aircraft trajectory mangement tools for the Single European Sky's ATM Research (SESAR) programme, and integrated positioning and navigation systems for for many applications including ITS. In 2013, Prof. Ochieng was elected Fellow of the Royal Academy of Engineering (FREng) in recognition of his exceptional contribution to engineering.
et al., 2017, GNSS/Electronic Compass/Road Segment Information Fusion for Vehicle-to-Vehicle Collision Avoidance Application., Sensors (basel), Vol:17
Ali BS, Ochieng WY, Zainudin R, 2017, An analysis and model for Automatic Dependent Surveillance Broadcast (ADS-B) continuity, Gps Solutions, Vol:21, ISSN:1080-5370, Pages:1841-1854
et al., 2017, A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults., Sensors (basel), Vol:17
et al., 2017, Integrated GNSS/DR/road segment information system for variable road user charging, Transportation Research Part C-emerging Technologies, Vol:82, ISSN:0968-090X, Pages:261-272
et al., 2017, Integrated method for the UAV navigation sensor anomaly detection, Iet Radar, Sonar and Navigation, Vol:11, ISSN:1751-8784, Pages:847-853