Adaptive Primary-Field Cancellation for Weak Target-Response Measurement in Underwater Active Electromagnetic Sensing Systems

Abstract

Underwater active electromagnetic sensing is effective in turbid and optically degraded environments, but weak target-induced secondary fields are often masked by strong transmitter-coupled primary fields. This paper proposes an Adaptive Hybrid-Gradient Least Mean Square (AH-GLMS) method for rapid primary-field cancellation and weak target-response measurement. The method combines a q-gradient update for fast adaptation with a classical gradient update for low steady-state residual error, and uses a modified sigmoid function to adaptively control the mixing factor between the two update modes. Simulation results show that AH-GLMS converges faster than the compared methods and achieves a steady-state output variance of 4.38 × 10^−3 V^2, close to the ambient noise variance, while maintaining the highest primary-field cancellation ratio over interference-to-noise ratio (INR) values from 5 dB to 30 dB. Laboratory pool experiments with a moving metallic target further confirm that AH-GLMS extracts the target-induced secondary-field response from the measured signal and achieves a steady-state residual variance of 7.90 × 10^−5 V^2. These results demonstrate its effectiveness for rapid weak-response measurement in underwater active electromagnetic sensing.