Abstract
Delivery of airborne precision guided vehicles to pre-designated targets has assumed much importance in recent times. Transfer alignment is concerned with estimation of misalignment with respect to the airborne platform. During first few seconds of the post ejection phase, the trajectory deviates from intended one. Estimation of this deviation in trajectory can also be mapped to the transfer alignment problem. Large misalignment angle makes the system nonlinear while usage of mother measurements in each iteration makes it time varying. Particle filter variants can be designed to improve the quality of estimates but the time complexity increases. This work explores different resampling techniques to find a way to decrease the average time to complete an iteration. This allows more room for parallel execution with a residual evolutionary particle filter that does away with resampling by evolving through several system dynamics, thereby performing better when the knowledge of system dynamics is poor. It is observed that when the two filters are run together, the estimation accuracy improves considerably. The scheme is particularly useful in the time critical post ejection phase.
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Chakraborty, S., Chattaraj, S. & Mukherjee, A. Performance evaluation of particle filter resampling techniques for improved estimation of misalignment and trajectory deviation. Multidim Syst Sign Process 29, 821–838 (2018). https://doi.org/10.1007/s11045-017-0472-1
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DOI: https://doi.org/10.1007/s11045-017-0472-1