Abstract
This paper aims to find an appropriate approach to improve estimation accuracy of bearings-only tracking (BOT) and Doppler bearing tracking (DBT) by making use of the constraint on target speed. Targets usually travel within a valid speed zone so this contextual information (speed inequality constraint) should hypothetically help tracking algorithms (filters) achieve better accuracy. However the inequality constraint filters, usually implemented using the rejection sampling approach, have high computational cost. This paper will study the accuracy improvement brought by the inequality constraint as well as the computational cost introduced in the BOT and DBT problems. Furthermore, we will also propose cost effective approach, which is the speed and range parameterized multiple model (MM) filter with different initial states in the valid range and speed zone. This MM-BOT/DBT, inspired from the range parameterized BOT (RP-BOT), applies the speed inequality constraint at track initial stage. Simulation test results show that the MM approach outperforms others in terms of estimation accuracy and computational efficiency.
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