The active sonar detection performance in shallow water is mainly restricted by the reverberation level. When target echoes are separable from reverberation according to Doppler shifts, comb waveforms with the bed‐of‐nails ambiguity function can achieve reverberation suppression. However, some comb waveforms present significantly low transmitting efficiency measured by the high peak‐to‐average power ratio (PAPR), which may severely affect the detection performance in a noise‐limited scenario. In order to effectively improve their transmitting efficiency, the authors propose an approach of comb waveform optimisation with low PAPR via alternating projection in this study. The main idea is based on designing projection constraint sets and corresponding projection operators to achieve the shaping of comb spectra. Hence, the approach has the capability to make a compromise between the transmitting efficiency and reverberation suppression performance. The PAPR control of geometric comb waveforms is implemented in simulations, which prove the validity of the approach.

Tone detection is crucial for passive sonar systems. Numerous algorithms have been developed for passive tone detection, but their effectiveness in detecting weak tones is still limited. To enhance noise resilience in passive tone detection, a broad-receptive field complex-valued structure named attention-driven complex-valued U-Net is proposed. Concretely, two attention mechanisms, namely, temporal attention and harmonic attention, are proposed to broaden the receptive field with high computational efficiency. Complex-valued operators are then introduced to mine both amplitude and phase information of tones. Additionally, a symmetric downsampling and upsampling strategy is proposed to improve the reconstruction accuracy of detailed time-frequency information. Overall, the proposed method demonstrates a strong robustness to noise and a strong ability to generalize. Experimental results on both simulated data and real-world data validate the superiority of the proposed attention-driven complex-valued U-Net against conventional U-shaped structures.

This paper describes a flexible micro-electro-mechanical system (MEMS) shear stress sensor, fabricated on a polyimide substrate using sputtering and a lift-off technique. The width of the nickel thermistor is minimized to several microns by an optimized manufacture process. The performance of the nickel thermistor is notably enhanced by heat-treatment during the fabrication. The sensor's characteristics are tested, including the temperature coefficient of resistance (TCR), time constant (cutoff frequency), and sensitivity. As a result of the optimized fabrication and the appropriate annealing heat-treatment, the TCR of the nickel thermistor is high, which has a considerable effect on the sensitivity; these techniques and results are an improvement on results in literature. The cutoff frequency test and sensitivity calibrations of the sensor were performed in a wind tunnel. The results show that the improved sensor with higher TCR and smaller size can be used in wind tunnel measurements effectively.

A flight data recorder (FDR) is an electronic recording device placed in an aircraft for the purpose of facilitating the investigation of aviation accidents. If an aircraft crashes into water, an underwater locator beacon (ULB), which is installed on the FDR, is triggered by water immersion, and emits an ultrasonic 10 ms pulse signal once per second at 37.5 kHz. This pulse signal can be detected by sonar equipment. However, the ULB signal only can be detectable 1–2 kilometers from the surface in normal conditions. Stochastic resonance (SR) is a rising theory in the field of weak signal detection. The classical stochastic resonance limits state that the input must be small-parameter and the sampling frequency must be 50 times higher than the signal frequency. It cannot be applied to the ULB signal detection. To resolve this problem, this paper presents a novel approach named mixing and normalizing stochastic resonance (MNSR). By mixing the ULB signal and normalizing SR system parameters, MNSR provides a new way to detect weak ULB signal. Meanwhile, we propose the parameters adjustment method of MNSR. We prove the effectiveness through numerical simulation. An experiment in a tank is employed to verify the practicability of this method.

This paper aims to simulate the underwater acoustic channel which affects the performance of acoustic communication of UUV. The acoustic channel can be described as a filter which has a specific transfer function. The transfer function is computable under normal mode model of acoustic propagation in medium. Then the received signal of UUV can be obtained by using convolution algorithm based on fast Fourier transform. This simulator can be used for testing the performance of UUV communication receiver in the laboratory.