Anti UAV Radar X-band Short-range Monopolar Radar With Advanced Detection And Early Warning Capabilities

  The DD-R34 X-band short-range monopolar radar integrates a fully solid-state, fully coherent, and pulse Doppler system. This system enables it to perform all-weather detection and early warning of "low, small, slow" targets. By leveraging machine learning and AI recognition technologies based on "micro-Doppler signatures" and "flight path features," the radar effectively detects and classifies a variety of targets. These targets include drones, light aircraft, helicopters, powered triplanes, airships, and airborne balloons, all while maintaining an extremely low false alarm rate. The radar is equipped with a two-dimensional phase scanning system. This system can be expanded into configurations such as "azimuth mechanical scanning + elevation phase scanning" or multi-polar arrays, thus meeting diverse application requirements. 

  The product is equipped with comprehensive target monitoring and analysis capabilities. These capabilities enable it to perform target positioning, trajectory display, and playback functions directly on the map. Simultaneously, it presents key parameters in real - time, such as the target's distance from the monitoring point, azimuth (the horizontal angle measured clockwise from a reference direction), elevation (the vertical angle above the horizontal plane), and speed.

  This system comes with built - in data recording and storage functionality. This means it can thoroughly save all target trajectory data, which includes details about the path the target has taken over time. It also stores radar status information, such as the operating mode, power levels, etc. This data storage supports subsequent data playback, allowing users to review past target movements, and query operations, enabling them to search for specific data points or time intervals.

  By leveraging AI recognition technology based on "micro - Doppler features" and "track features," the product showcases powerful target classification and identification capabilities. It can accurately distinguish between various target types. These include drones, which are unmanned aerial vehicles used for a variety of purposes; birds, which are natural flying organisms; people, who may be detected in certain surveillance scenarios; and vehicles, which can be on - ground or in - air depending on the context of the monitoring.

The system incorporates advanced machine learning technology. This allows it to adapt autonomously to the current environment. Instead of requiring manual parameter adjustment, it can start operation directly. This feature is highly beneficial as it reduces the need for expert intervention and allows for seamless operation in different scenarios.

  To guarantee reliable all - weather operation, the product is equipped with cloud and rain noise suppression capabilities. These capabilities effectively eliminate interference caused by adverse weather conditions. Cloud cover and rain can often disrupt the signal and introduce noise in the monitoring process, but this product can overcome these challenges.

The software interface of the product offers flexible parameter configuration options. Users can adjust settings according to their specific needs. For example, they can modify the elevation coverage, which determines the vertical range of the monitoring area; the target update rate, which affects how frequently new target data is received and processed; and the monitoring range, which defines the maximum distance at which the system can detect targets.

  In addition, the product has automatic compensation functions for independent positioning, orientation, elevation, and roll angles. These functions ensure measurement accuracy. Any changes or inaccuracies in these angles due to external factors, such as vibrations or changes in the mounting position, can be compensated for automatically.

  During system operation, users can make full use of the real - time status monitoring functionality. This enables them to closely monitor the equipment's working conditions. By doing so, they can ensure the stable and efficient operation of the entire system, quickly identifying and addressing any potential issues that may arise.