A Novel Underwater Location Beacon Signal Detection Method Based on Mixing and Normalizing Stochastic Resonance

Abstract

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.Sensors 2020, 20, 1292 2 of 15 classical stochastic resonance cannot detect the large-parameter (large-amplitude or high-frequency) signal directly. To make SR more practical, researchers have proposed several large-parameter stochastic resonance (LPSR) methods, such as twice sampling stochastic resonance [11], re-scaling frequency stochastic resonance (RFSR) [13], system parameters normalization transform stochastic resonance, or parameters normalized stochastic resonance (PNSR) [14]. These methods transform the large-parameter signal into a small-parameter signal which satisfies the small-parameter conditions numerically. The disadvantage is the requirement of a high sampling frequency (at least 50 times to the signal frequency, and generally 200 times or more). It is hard to achieve in engineering application scenarios when the weak signal frequency is high. Another LPSR method, modulated stochastic resonance (MSR) [15], modulates the high-frequency weak signal immersed with noise to a low difference frequency signal to implement LPSR. MSR requires a long signal duration to ensure that the duration contains at least two complete periods of the low difference frequency signal. To realize the detection of ULB signal which is high frequency and short pulse by SR method, mixing and normalizing stochastic resonance (MNSR) is proposed in this paper. Through mixing the ULB signal with a carrier signal, the ULB signal detection can be replaced by the "low" frequency difference signal detection. Here, the "low" means the difference signal frequency is lower than the ULB signal frequency and the sampling frequency. Under the restriction that the sampling frequency must be 50 times higher than the signal frequency, MNSR allows the sampling frequency to be much lower than RFSR, which detects ...