Title: Power-Efficient Cognitive Radar for Multi-Target Tracking in the Presence of Unknown Disturbances

Abstract: This study introduces a cognitive radar (CR) architecture utilizing massive multiple-input multiple-output (MMIMO) systems to monitor multiple aircraft amidst unknown disturbances. Recognizing that uniform power distribution is inefficient across fluctuating signal-to-noise ratios (SNRs), the proposed framework integrates an adaptive waveform design facilitated by Partially Observable Monte Carlo Planning (POMCP). The system assigns a distinct POMCP tree to each target, enabling effective state prediction. These forecasts drive a constrained optimization process that strategically allocates transmit energy, prioritizing weaker targets without compromising the power levels required for stronger ones. Experimental outcomes demonstrate that the POMCP-based approach boosts the detection probability for low-SNR targets from 0.6 to approximately 0.9. Furthermore, it delivers superior tracking precision for the weakest target compared to both non-adaptive orthogonal waveforms and a cognitive baseline employing uniform power with POMCP.

Source: arXiv Generated at: 2026-06-03 00:00:00 UTC