This final report gives an account of the activities carried out and the results produced in the three-year Armed Forces' project Sensor Systems for Urban Operations. In the project studies are conducted of how various combinations of sensor systems can be made to cooperate in order to result in improved situation awareness in the urban environment. These activities include important research tasks of designing robust data fusion methods and algorithms for detection, classification, and tracking of human movements, based on multisensor data, and furthermore the development of methods for automated detection of deviations from a normal state. The research efforts in the project are focused towards giving research backing within the following military need areas: Continuous Surveillance, Crowd Surveillance, and Blue Force Tracking. The project participates in several international collaborations, and by co-financing of four EU FP7 projects the project gets access to the research and the results generated in these. Furthermore, we are participating in the NATO group SET-153 RTG-083 Multi-sensor integration in urban operations, where a multi-sensor experiment carried out in the autumn of 2011 will produce important knowledge of how sensor co-operation can give increased situation awareness. New detection algorithms for multi-target tracking of humans in a complex urban environment have been developed and evaluated. Detection based on classifiers according to the boosting principle has turned out to be promising, as have classifiers using several cooperating sensor views that can handle partly concealed persons. Moreover, new tracking algorithms using colour attributes have improved the stability of the association between tracks and detections. Detection and tracking in complex urban environments are still active fields of research, and presently no general solutions to the problem are found. Aspects of acoustic propagation in urban environment have been given attention and experiments with acoustic arrays have been carried out. An underlying architecture for sensor integration over extended urban areas has also been designed and has formed the basis of requirement setting for distributed algorithms and communication channels. An automated method for determination of normal state and anomaly detection, based on a Hidden Markov Model (HMM) and data from sensor detections, has been developed in order to be able to detect threat states (anomalies) in crowds, as e.g. riots, fights, and assaults. Data from trials with simultaneous recordings with visual cameras, thermal IR cameras, acoustic sensors, and 3D laser have formed the basis of the development. Under simple and relatively stationary environmental conditions our method has a detection probability of 90%. A useful sensor combination is optical and acoustic sensors. High sound levels often indicate threat situations, while the optical sensor gives information about the number of individuals and their activities. Fusion of optical and acoustical sensor data raises the possibility of more robust position determination and anomaly detection. Work has continued on studying and developing methods and system concepts for automatic detection of interesting, deviating events and course of events in urban environment. A framework for fusion of anomaly detections has been developed, enabling simultaneous handling of different forms of attributes and target tracks, as well as being able to fuse detections over time. The sub-project Blue Force Tracking investigates how new techniques may be used for the tracking of the movements of one's own soldiers in buildings without GPS coverage. We have with the test system CHAMELEON, an in-house development consisting of a stereo camera and an IMU, experimentally shown the possibility of a soldier, using the SLAMtechnique, to determine the soldier's own position and simultaneously construct a map of the interior of the building. We have also developed a completely new, "silent" RF-based method for positioning of one's own soldiers in buildings. With a one-dimensional test system, designed in-house, we have been able successfully to verify, in controlled experiments, the functionality of the system concept.