## 1 Introduction  
With the advancement of materials science and computational theory, the use of Autonomous Underwater Vehicles (AUVs) in marine industries has significantly increased. Compared to manned/remotely operated underwater vehicles, AUVs have demonstrated superior reliability and cost-effectiveness in executing underwater missions [1]. To efficiently and stably accomplish complex tasks--such as pipeline inspections for oil and gas industries, oceanographic observations, bathymetric surveys, military applications, high-resolution seabed inspections, mapping, commercial explorations, and neutralization of seabed mining areas--in unknown underwater environments, formation control of AUVs has emerged as a critical research focus [2]. Concurrently, theories related to radio frequency, optical, and acoustic communication have been continuously developed to enhance data transmission capabilities between AUVs in underwater environments [3]. Among these, active and passive positioning between AUVs is regarded as a fundamental prerequisite for mission execution [4]. For AUV identification and localization, traditional transponder-based methods face limitations in deployment/maintenance costs and device power constraints. Optical approaches are restricted by critical factors such as lighting conditions, turbidity, and feature richness [5], with localization accuracy varying by up to an order of magnitude across different vision-based algorithms [6]. Meanwhile, sonar-based simultaneous localization and mapping (SLAM) techniques incur high computational costs and exhibit significant uncertainties under complex environmental conditions [7]. To address these challenges, a series of novel AUV underwater identification and localization methods have been continuously proposed. These include the establishment of underwater artificial landmarks detectable by cameras or optical sensors [8], though vision-based solutions are limited to short-range applications. In response, [PERSON] et al. [9; 10] introduced the concept of a passive Acoustic Identification Tag (AID). This tag reflects unique acoustic characteristics when interrogated by sonar pulses, enabling it to function as a low-maintenance, cost-effective navigation aid. Inspired by passive surface acoustic wave RFID tags [11], AID tags modulate parameters such as acoustic material type, arrangement, and thickness to generate distinctive acoustic signatures. Building on this concept, [PERSON] et al. [12] developed an AID tag capable of infinite ultrasonic wireless power transfer and backscatter-based localization. Concurrently, leveraging SonarBell Corporation's research on polymer target acoustic scattering [13], [PERSON] et al. [14] experimentally validated the feasibility of passive acoustic markers utilizing Rayleigh wave resonance in biaxially oriented acrylic spheres. [PERSON] et al. [15] further optimized the design of multilayered hemispherical shell AID tags. Following this methodology. [PERSON] and [PERSON] [16] created a PMUT-based ultrasonic tag with 136-day battery life (CR2032) for sensor data transmission in RF-limited/noisy environments, enabling low-power IoT solutions. [PERSON] et al. [17] investigated the application and optimization methods of this approach in turbid waters for navigation purposes; subsequently, in their field trials [18], the team further demonstrated the viability of concentric acrylic-based AID tags for precise AUV navigation and positioning. [PERSON] et al. [19] established the feasibility of time-domain echo coding using four-layer elastic spherical shells. Most recently, [PERSON] et al. [20] achieved a breakthrough by combining periodic rib-plate and helical groove structures with polymethyl methacrylate (PMMA) multi-sphere assemblies, successfully integrating time-frequency domain scattering features with geometric-elastic characteristics. This work verifies the practicality of acoustic coding and pioneers new approaches for intelligent underwater target recognition.