Final report: Simulation based sensor system assessment – Assessment of reconnais-sance performance for unmanned systems


  • Fredrik Näsström
  • Jonas Allvar
  • David Bergström
  • Robert Forsgren
  • Per Grahn
  • Johan Hedström
  • Morgan Ulvklo

Publish date: 2014-12-31

Report number: FOI-R--3993--SE

Pages: 56

Written in: Swedish


  • Assessment
  • sensor systems
  • simulation
  • modeling
  • unmanned systems


The task for the SIMSENS project (Simulation based sensor system assessment) is to further develop methodology to assess sensor systems. When doing assessment of a sensor system a good method is required that can take into account various factors such as: the sensor system, tactics, environment, economy, human system interaction, education etc. In this study, we have used a method called COAT/TVS method and further developed the method and tools for sensor assessment. To test the enhanced assessment methodology and tools an application example has been studied. The example we have chosen is about assessing the ability of three relatively different UAV systems in two different use cases. To be able to discuss methods and tools, we have chosen to work only with unclassified information. UAV systems that have been assessed may differ slightly from the actual UAV systems, as data in some cases has been lacking. In these cases, reasonable values have been used instead. The project also has the task of developing a simulation environment for the evalu-ation of sensor systems. Simulation environment to be developed further for this is MSSLab (MultiSensorSimuleringsLab). In the simulation environment, various sensors are simulated in various environments, weather conditions and time peri-ods. The simulation environment has been used in the assessment of UAV systems to simulate sensors in the various use cases. In order to make high-quality simula-tion of sensor systems all simulation models such as terrain models, target objects, materials classification, scene simulation and sensor models are required to have high quality. This work includes validation of sensor simulations with data from real sensor measurements.