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In collaborative multi-platform observation systems, radar-based localization of non-cooperative aerial objects is often limited by obstacles, sensing-range constraints, and measurement uncertainties. Moreover, in global navigation satellite system-denied environments caused by interference, spoofing, or other disruptions, the position and velocity estimates of aircraft can be affected by significant noise. First, a velocity-aided collaborative navigation filtering algorithm using inter-node range and radial-velocity measurements is developed for multiple cooperative platforms. Subsequently, a velocity-aided localization algorithm is employed to estimate the object’s position under various measurement conditions. Finally, an interacting multiple model filtering and fusion method is utilized to fully integrate available observational information. Simulation and analysis results demonstrate that the proposed method outperforms the range-only baseline and several velocity-aided filtering baselines in the tested scenarios.
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Jiang et al. (2026) studied this question.
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