Smart Surveillance Radar Water Area Tracking Solutions with Minimum Range of ≤200m and Security Warning

Water Area Monitoring Multi-sensor System

The multi-dimensional joint perception system for water monitoring is an all-encompassing, cutting-edge solution that integrates advanced monitoring radar, automatic ship identification (AIS), optical video, and innovative unmanned aerial vehicles as its core sensory tools. This robust system excels in detecting, identifying, and continuously tracking even the smallest targets in challenging aquatic environments. It further enhances surveillance capabilities with radar-guided optical equipment for precision tracking, photography, evidence gathering, and real-time alert notifications. By leveraging the power of multi-dimensional data fusion, sophisticated image recognition, and AI-driven algorithms, it swiftly identifies unauthorized activities such as illegal fishing, sand mining, maritime smuggling, and unlawful immigration. This remarkable system autonomously executes search and discovery, issues alerts, and compiles evidence, finding applications across a breadth of sectors including smart fishery governance, intelligent fishing ports, advanced sand control, coastal defense operations, offshore oil and gas exploration, wind power generation facilities, and bridge collision prevention.


Centers Mobile Platform

LW-R25-SG solid-state pulse compression water monitoring radar. This radar represents a technological advancement over its predecessor, the LW-R25-SC model, boasting superior technical specifications. It employs state-of-the-art technologies such as a solid-state transmitter, digital signal processing, and multi-waveform pulse compression, alongside STC features. This results in an extended detection range, minimal blind spots for close-range detection, high precision tracking, and unmatched target accuracy. Its versatile application spans sectors such as smart fishery management, intelligent fishing ports, modern port operations, and border defense initiatives.