This final report gives an account of the activities carried out and the results in the three-year Armed Forces' project Surveillance Systems. The project has studied how various sensor systems can co-operate to accomplish improved situation awareness in the urban environment. With multi-sensor data as a base, important research tasks are to devise robust data fusion methods and algorithms for detection, classification, and tracking of human movements and to develop methods for automated detection of deviations from the normal state. The research efforts of the project have been concentrated towards the following military need areas: continuous surveillance, anomaly detection, and Blue Force Tracking. In the area of continuous surveillance we have developed the methodology for combining sensor data, target tracking based on multiple sensors like cameras and microphones, as well as sensor data evaluation. In smaller study segments, we have also analysed how radar and laser based sensors function as component parts beside other sensor types like cameras and microphones. Methods for anomaly detection have been developed and evaluated. We have shown that the probability of detection is significantly improved with sensor fusion compared to using only one or the other of the cameras. The reason is that with several cameras the calculations can be based on a greater amount of information about the area in question. Moreover, the methods are general enough to be used for various system solutions. This is especially the case for the number of cameras in the network, the type of input data and the type of coordinate system. In the area of Blue Force Tracking, we have investigated new techniques for following one's own soldiers in buildings where GPS coverage is missing. With our own-developed test system Chameleon, we have successfully pointed to the possibility to determine one's own position and simultaneously to construct a map of the interior of the building by using the SLAM-technique (Simultaneous Localization and Mapping). With the integrated system, consisting of thermal infrared cameras, visual stereo-camera and IMU, we have in experiments shown that the estimate obtained with the help of supplementary infrared cameras is very close to the true trajectory. In 2014, a real-time system consisting of a visual stereo camera and IMU, has been developed and tested with good results. It has been possible to investigate, in experiments with an own-developed test system, the potential of our unique RF-based method for silent positioning of one's own soldiers in buildings. The test system, which was one-dimensional in its first version, has been developed further this year to enable three-dimensional positioning, which means implementation of sequential transmission and reception in hardware and software. Experiments carried out at the test site MSS Kvarn show that 3D-positioning works in a complex urban environment. The project has been engaged in several international co-operations, four EU FP7 projects and participated in the two NATO groups Multi-Sensor Integration for Urban Operations and Battlefield Acoustic Sensing, Multi-modal Sensing and Networked Sensing for ISR Applications. Participation in the NATO groups has given us new knowledge of how sensors and sensor systems are suitably combined to accomplish improved situation awareness in military operations.