This article investigates the underwater node dynamic localization and prediction problems in a dynamic sensor network. Node localization in the Internet of underwater things is the basis of target tracking and ocean monitoring. At present, most of the node location algorithms assume calm sea and fixed node location. However, the current velocity is uncertain in space and time. The nodes are drifted with the current motion. Therefore, most of the localization algorithms lose efficacy in the actual marine environment. In order to solve the above problems, a node dynamic prediction algorithm is proposed. First, the node mobility model is improved, which is more suitable for the actual marine environment. Second, a frequency-based anchor node prediction algorithm is designed to improve anchor node location accuracy. Third, when the ordinary node receives the signals sent by anchor nodes of different depths, a deep information-based weighted fusion method is designed for the ordinary node localization in order to mine more information in each direction. Finally, location and prediction simulation in sensor networks is carried out. The results show that the proposed node localization and prediction algorithm is more accurate than SMLP and high-precision localization with mobility prediction algorithms and prove the enhanced effect of our method in dynamic marine.

Aiming at the problems of excessive fluctuation and long adjustment time when LLC resonant converter encounters load mutation in traditional control strategy, which seriously affects the normal use, an improved self-disturbance control strategy based on sliding mode control is proposed. The mathematical modeling of LLC resonant converter is carried out by using the method of extended description function to obtain the transfer function of LLC resonant converter. On the basis of linear self-disturbance control, sliding mode control is introduced as the control rate. Through simulation, the steady-state characteristics and dynamic characteristics of LLC resonant converter under three different control strategies of PI (proportional integral controller), LADRC (linear active disturbance rejection control), and SM_ADRC (sliding mode active disturbance rejection control) are compared and analyzed. The simulation results show that the sliding mode active disturbance rejection control is superior to the other two control strategies in improving the response speed and anti-interference ability of LLC resonant converter, with a response time of only 2ms and a ripple of only 0.04V. A small power experimental platform with an output power of 192W is built. The experimental results show that LLC resonant converter can be restored to steady state in a short time by using sliding mode active disturbance rejection control, which effectively improves the dynamic characteristics of the system.

This paper investigates the ordinary nodes localization problem by utilizing mobility-constrained nodes. The mobility-constrained nodes are anchored to the seabed by cables in underwater sensor networks. Many studies assume these mobility-constrained nodes’ locations as fixed, not considering their mobile properties. In the actual marine environment, they usually deviate within a restricted radius due to current fluctuations, rope tension, their gravity, etc., thus causing inaccurate localization. Moreover, underwater communication is through acoustic waves. The acoustic propagation is slow, and the propagation delay cannot be ignored. To solve these problems, particle system based localization with delay compensation is proposed, and it contains two parts. In the first step, the prior velocity information based delay compensation algorithm is designed to get the actual motion location of the target at the sampling moment. In the second step, based on the first step, the particle system based localization algorithm is proposed to narrow the localization range, where the characteristics of mobility-constrained nodes are considered. Finally, localization simulation is presented to show the effectiveness of our proposed algorithm. The proposed particle system based localization with delay compensation algorithm has higher accuracy and is more suitable for the actual underwater scenario.

When using pulsed ultra‐wideband radar (UWB) noncontact detection technology to detect vital signs, weak vital signs echo signals are often covered by various noises, making human targets unable to identify and locate. To solve this problem, a new method for vital sign detection is proposed which is based on impulse ultra‐wideband (UWB) radar. The range is determined based on the continuous wavelet transform (CWT) of the variance of the received signals. In addition, the TVF‐EMD method is used to obtain the information of respiration and heartbeat frequency. Fifteen sets of experiments were carried out, and the echo radar signals of 5 volunteers at 3 different distances were collected. The analysis results of the measured data showed that the proposed algorithm can accurately and effectively extract the distance to the target human and its vital signs information, which shows vast prospects in research and application.