The cost of an unattended ground sensor system is based on two factors: the number of sensor nodes used and, the complexity of each sensor/communications node. The tracking accuracy of the sensor network is a trade off between the density of the network and the accuracy with which the sensor nodes can determine the position or bearing of the target. Assuming acoustic sensors, the errors reduce, primarily, to timing errors, within each of the sensor nodes. Therefore that understanding the timing errors within a network of acoustic nodes is a factor in determining system cost for a given level of information fidelity. This paper explores the error mechanisms within and without each of the sensor nodes thus identifying the critical sub systems where engineering effort would be most effectively directed.
The nature of many current Intelligence, Surveillance, Target Acquisition and Reconnaissance (ISTAR) sensor systems requires that they are controlled at an operational or strategic level. The trend towards asymmetric/urban warfare has created the necessity for tactical commanders to be empowered with a similar ISTAR capability but over a reduced area. The variable temporal, spatial and cost constraints imposed by each scenario requires an adaptable organic sensory system to be developed to support the tactical commander. Unmanned Disposable Organic Sensor Networks (DOSNs) are promising to provide sensory solutions in many tactical situations. However in order to develop a suitable DOSN it is necessary to identify the optimum realisation to meet the tactical commanders requirements. In this paper the work conducted by QinetiQ for elements of the UK MOD is discussed. This includes: 1) A method for assessing the value of each specific realisation of a DOSN against a range of scenarios. 2) Description of models used to generate an understanding of the capability of DOSN systems. 3) Description of an experimental DOSN system with associated trial results and plans to validate the models discussed above. The technical approach employed could also be used to assess the applicability of DOSN systems across a range of other military ISTAR requirements.
Major advances in base technologies of computer processors and low cost communications have paved the way for a resurgence of interest in unattended ground sensors. Networks of sensors offer the potential of low cost persistent surveillance capability in any area that the sensor network can be placed. Key to this is the choice of sensor on each node. If the system is to be randomly deployed then non line of sight sensor become a necessity. Acoustic sensors potentially offer the greatest level of capability and will be considered here. In addition, there is a trade off between sensor density and tracking technique that will impact on cost. As a passive sensor, only time of arrival or bearing information can be obtained from an acoustic array, thus the tracking of targets must be done in this domain. This paper explores the critical step between array processing and implementation of the tracking algorithm. Specifically, unlike previous implementations of such a system, the bearings from each frequency interval of interest are not averaged but are used as data points within a Kalman filter. Thus data is not averaged and then filtered but all data is put into the tracking filter.
This paper describes the development of a tool that predicts the coverage and performance of sensor networks. Specifically it examines weapon locating radars and acoustic sensors in different terrain and weather conditions. The computer environment and multiple sensor models are presented. Fusion of sensors takes multiple predicted accuracy metrics from the single sensor performance models and combines them to show networked performance. Calculations include Cramer-Rao lower bound computation of the sensors and the fused sensors source location error. Results are presented showing the outputs of the models in the form of sensor accuracy maps superimposed onto terrain maps.