Multitarget passive coherent location with transmitter-origin and target-altitude uncertainties - Tharmarasa, R.; Subramaniam, M.; Nadarajah, Nandakumaran; Kirubarajan, T.; McDonald, M. (2012)
Passive coherent location (PCL) systems, which use existing commercial signals (e.g., FM broadcast, digital TV) as the illuminators of opportunity, is an emerging technology in air defence systems. PCL systems have many advantages such as low cost, covert operation, and low vulnerability to electronic countermeasures, over conventional radar systems. However, the limitations of PCL include lack of control over illuminators, limited observability, and poor detection due to low signal-to-noise ratio (SNR). This leads to high clutter with low probability of detection of target. Also, it is possible to transmit through multiple transmitters the same signal/frequency inside the coverage region of the receiver. Even though using multiple transmitters will facilitate better estimates of the target states due to spatial diversity, one cannot use these measurements without resolving transmitter- and measurement-origin uncertainties. Another limitation is that the elevation measurement, which is required to estimate the target altitude, is not available in most currently available PCL system receivers. In this paper, multiple target tracking algorithms for PCL systems are derived to handle low probability of detection and high nonlinearity in the measurement model due to high measurement error. Also, tracking algorithms are proposed to track multiple targets by resolving transmitter-origin uncertainty. Finally, algorithms are proposed for fusing multiple PCL system estimates by incorporating the altitude estimate uncertainty in order to improve the tracking accuracy and to increase the area coverage. The major contributions of this paper are the new algorithms for tracking using PCL systems with transmitter-origin and target-altitude uncertainties. The feasibility of using transmitters of opportunity for tracking airborne targets is shown on simulated and real data sets.