Detecting small undersea and buried targets, such as unexploded ordnances and sunken unmanned vehicles, is vital for protecting marine ecosystems and ensuring waterway security. Challenges arise from the spatial variability of acoustic scattering from these targets, coupled with significant reverberation interference from sediment layers, which reduces the signal-to-reverberation ratio (SRR) and hinders search efficiency. To address these issues, we propose an advanced high-resolution two-dimensional (2D) spatiotemporal multi-input multi-output (MIMO) detection method designed explicitly for buried targets. This approach employs a compact low-frequency MIMO array and an orthogonal frequency-modulated pulse train signal crafted under sonar-environment constraints. To enhance the target irradiation range of our method, a 2D point spread function is developed that aligns with the acoustic scattering characteristics of cylindrical targets while effectively suppressing reverberation interference. Experimental results demonstrate that the proposed method can double the target irradiation range, enhance the SRR by over 12 dB, and increase detection probability by at least 37% compared with conventional detection techniques.

Transmitting waveform design and signal processing method optimization are effective ways to improve a sonar system’s detection performance. In this study, the spectrum and ambiguity function characteristics of pulse trains of frequency modulation (PTFM) signals were deduced and analyzed to address the problem of serious reverberation interference in the detection of low-speed targets in shallow water environments. The action mechanisms of PTFM signal parameters on the comb spectrum and bed of nails ambiguity function were identified. PTFM signal parameters were designed according to reverberation suppression requirements. The threshold was calculated using the estimate-before-detect method, and the comb spectrum waveform cognitive filtering detection algorithm is proposed. The simulation and lake experimental results show that the PTFM signals’ reverberation suppression ability for low-speed targets was better than it was for stationary or high-speed targets. The proposed method has good universality, which can improve the output signal-to-reverberation ratio (SRR) by more than 6 dB.

Wideband signals exhibit significant advantages in reverberation suppression, range resolution, and target parameter estimation. Consequently, echoes acquired through wideband active sonar provide rich target information, facilitating tasks such as target detection and classification. However, as range resolution increases, target echoes spread across multiple range bins, resulting in energy accumulation loss and a reduced signal-to-reverberation ratio (SRR) within individual range cells, which ultimately degrades detection probability. To address this challenge, this paper proposes a detection method based on inter-frame mutual information (IFMI) in the range-Doppler (R-D) spatial domain. Received echo signals are segmented into frames and mapped into the R-D domain, forming multi-frame R-D subspace matrices. IFMI is introduced to quantify data association states between consecutive frames. This is achieved by computing the mutual information between corresponding rows of adjacent R-D subspace matrices. The minimum IFMI is designed as the final test statistic and compared against a decision threshold to achieve target detection. Furthermore, the proposed method preserves target information within the R-D domain. The extremum positions of the IFMI can be utilized to estimate target parameters, thus avoiding extensive two-dimensional searches in the R-D domain. The efficacy and superiority of the proposed method were validated through simulations and experimental analyses. The simulation results demonstrate that the proposed method significantly improves the detection performance for extended targets under low SRR conditions, achieving a detection probability of 85% even at -12dB SRR. Experimental results further verify that, compared to four existing methods, the proposed method increases the detection probability by at least 17% and reduces the false alarm probability by 10%.

Sonar detection of small undersea targets remains challenging owing to the weak target echo and substantial seabed reverberation interference. Dolphins possess a sophisticated biological sonar system that is superior to advanced sonars for detecting and identifying targets in complex environments. Based on dolphin’s bionic pulse for echolocation, a novel method for enhancing echo detection in the bionic-pulse fractional Fourier transform (FrFT) domain is proposed to reduce reverberation interference when detecting undersea targets. First, the bionic detection signal parameter is designed, and the optimal-order FrFT spectrum is derived. Then, based on the characteristics of the bionic bipolar signal’s FrFT spectrum, a FrFT point spread function is generated to enhance the target echo and suppress reverberation interference. Combined with the bipolar bionic pulse sonar processing algorithm in the FrFT domain, this approach shows improved undersea-target detection performance. Finally, experimental results show that the output signal-to-reverberation ratio of a target achieved using the proposed method is >9 and 6 dB higher than those achieved using the twin inverted pulse sonar and space–time combined high-resolution processing methods, respectively, irrespective of high-frequency or low-frequency twin inverted pulse signal utilization. Therefore, the experimental results demonstrate the effectiveness and high accuracy of the proposed method.

USBL have been widely used in underwater operations. Firstly, the principle of ultra short baseline positioning is introduced. The signal processing process of the ultra-short baseline positioning system is provided. Then, signal waveform based on COSTAS frequency hopping signal is designed. Frequency hopping signal model is provided. The time and frequency resolution capabilities of the signal is analyzed. Finally, correlation simulation analysis is conducted on 4 COSTAS frequency hopping signals. The simulation results show that the COSTAS frequency hopping signal has good autocorrelation and cross correlation characteristics, and can be used as a signal waveform for ultra-short baseline positioning multi-target.