Application of adaptive background equalization in passive detection of underwater targets

Addressing the challenges of weak target detection in passive sonar within complex marine environments, such as susceptibility to noise interference and track fragmentation, this paper studies the application of adaptive background equalization techniques in passive detection. An adaptive parameter adjustment according to beam bearing angle and environmental conditions is introduced to improve the traditional Order Truncate Average (OTA) algorithm, enabling spatio-temporal adaptive suppression of non-uniform noise and interference. Combined with the cumulative detection capability of the Hough transform, continuous target tracks are extracted from the equalized bearing-time recording (BTR) plots. The results of simulations and sea trials show that the processing method relying on adaptive background equalization can significantly enhance target detection performance and tracks’ continuity under conditions of low signal-to-noise ratio (SNR) and substantial interference. These results verify this technology’s effectiveness and engineering application value in the passive detection of underwater targets.