Target-Protected Multiscale GLRT-CUSUM Detection for Low-SNR Vector Magnetic Anomalies on Ocean Buoys

Vector magnetic anomaly detection on ocean buoys is challenged by attitude changes, non-stationary backgrounds, and weak targets that adaptive filters may absorb. We propose an online target-protected framework combining attitude compensation, constant-false-alarm-rate normalized innovation squared (CFAR-NIS) threshold adaptation, target-dwell gating, whitening based on a target-free calibration covariance, and weighted multiscale generalized likelihood ratio test-cumulative sum (GLRT-CUSUM) fusion. The target-protection mechanism constrains covariance adaptation and the effective Kalman gain during suspected target intervals, while dual-threshold confirmation suppresses isolated background spikes. We evaluated the method using publicly available buoy attitude and triaxial magnetometer background data with injected ship magnetic signatures under semi-physical conditions. At SNR ≈ 2.7, 200 paired Monte Carlo trials yielded a detection probability of 0.965, a background false-alarm rate of 0.045, and an average delay of 208.3 samples. Compared with standard and adaptive Kalman filtering, orthogonal-basis-function (OBF), minimum-entropy, and spectral-residual CUSUM baselines, the proposed method significantly improved detection probability and shortened delay. Its false-alarm rate was comparable to OBF and SR-CUSUM but higher than those of standard KF, adaptive KF, and minimum-entropy detection. Validation with real operational sea-trial data remains necessary.