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The problem of single-sensor bearings-only tracking continues to present challenges to tracking algorithms, particularly in certain difficult scenarios such as ones with high bearing rates. In such scenarios, the performance of the recently introduced shifted Rayleigh filter (SRF) is compared with that of other techniques such as extended Kalman filter (EKF), unscented Kalman filter (UKF) and particle...
In this paper a hybrid Kalman filter is derived for the tracking of ground based targets. The propagation is performed using unscented Kalman filter equations, while the updates are performed using extended Kalman filter equations. The novel feature of this hybrid filter is that terrain information has been incorporated to improve the accuracy of state estimates. This information, termed trafficability,...
The exploitation of bistatic Doppler measurements for multistatic tracking is considered. It is found through simulation, that, while the velocity estimation of the standard extended Kalman filter is improved in monostotic situations and multistatic situations where measurement errors are small, a degradation in performance is observed in multistatic situations where the measurement errors are realistically...
This paper considers the recursive estimation of emitter location using time difference of arrival measurements formed by the correlation of signals received by two unmanned aerial vehicles. The time difference of arrival measurement defines an hyperbola of possible emitter locations. This hyperbola is used as a measurement in a nonlinear Alter. The performance of two such filters, an extended Kalman...
Data assimilation in the context of puff based dispersion models is studied. A representative two dimensional Gaussian puff atmospheric dispersion model is used for the purpose of testing and comparing several data assimilation techniques. A continuous nonlinear observation model, and a quantized probabilistic nonlinear observation model, are used to simulate the measurements. The quantized model...
This paper describes two tracking filters based on the use of kinematic information (velocity, acceleration), in addition to usual position measurements. This kinematic information allows for more advanced filtering methods, reducing error especially on maneuvers. In the paper we will show two different Kalman filter exploiting this information, and compare them with regards to accuracy, computational...
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