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974-Clear-air radar video fusion solution

Name: 974-Clear-air radar video fusion solution
Brand: Orihard
SKU: 974
Availability: InStock
Rating: 5 (1 reviews)

Item No.: 974

The Radar-Vision Fusion System integrates 200m-range radar (0.1m accuracy, ±8m/s speed detection) and 4K optical camera (25mm F1.8 lens, H.265 encoding) for all-weather surveillance.

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Description

1. Detailed explanation of the performance indicators of radar products

1. Physical properties

Product size: 200mm×200mm×250mm (excluding connectors), compact design suitable for space-constrained scenarios (such as vehicle, drone).
Interface compatibility: It supports hardware interfaces such as CAN bus, RS485, and network port, as well as Modbus TCP/RTU, Canopen and other protocols, which is easy to integrate into industrial automation or intelligent systems.

2. Detection accuracy and range

Distance accuracy: 0.1m, which can accurately identify the target position, and is suitable for scenarios that require millimeter-level positioning.
Standard range: 200m, covering the needs of medium and short distance detection, and the speed measurement range can be extended to (-8m/s, 8m/s) to meet dynamic target tracking (such as vehicle and pedestrian speed monitoring).
Angular accuracy: 0.125°, angular measurement range (-15°, +15°), for high-precision scanning with narrow viewing angles, suitable for focusing on specific area targets (e.g. vehicle steering detection at intersections).

3. Data output capability

Output frequency: 20Hz, 30Hz, 50Hz optional, high-frequency output (such as 50Hz) is suitable for scenarios with high real-time requirements.

2. Detailed explanation of camera performance indicators

1. Imaging core parameters

Sensor & Resolution: 1/1.8" CMOS sensor, 3840×2160 (8 million pixels), auto-zoom; It supports 4K ultra-high-definition image quality and has strong detail capture capabilities (such as license plate and face feature recognition).
Optical parameters: 25mm focal length + F1.8 large aperture, field of view 19.3°×15.5°×11.6°, suitable for medium and long-distance close-up monitoring

2. Environmental adaptability

Noise Reduction and Fog Transmission: Support 2D/3D digital noise reduction, super noise reduction, with electronic/optical fog transmission function, it can still maintain clear imaging in harsh environments such as haze and strong light.
Wide dynamic range and fill light: wide dynamic range adapts to light and dark contrast scenes, infrared fill light ≥ 200m, to achieve full dark night vision monitoring.

3. Functionality and compression standards

Intelligent adjustment: Support automatic white balance, electronic image stabilization, saturation/brightness and other parameters to adapt to different lighting environments.
Video compression: Compatible with H.265/H.264 encoding formats, reducing storage and transmission bandwidth requirements while ensuring image quality.

3. Thunder Video Fusion Solution: Technical Path and Application Value

1. Convergence of technical logic

dimension	Radar advantage	Camera advantages	Convergence value
Environmental adaptability	It is not affected by light, rain and snow, and works around the clock	Provide high-resolution visual information	Compensate for the imaging shortcomings of the camera in bad weather
Targeting	Accurately measure distances, speeds, angles	Identify target shapes, colors, types	Combining radar positioning and camera recognition to improve the accuracy of target classification
Data complementarity	Active detection, strong penetration	Passive imaging with rich detail	Reduce the false positive rate of a single sensor

2. Convergence technology path

Data Synchronization: Clock calibration ensures that the radar (range/speed) is consistent with the camera (image frame) timestamp to avoid target position deviation.
Coordinate calibration: Establish the conversion relationship between the radar scanning coordinate system and the camera pixel coordinate system.
Target association: Kalman filter and other algorithms are used to associate and match the target trajectory detected by the radar with the target features recognized by the camera.
Decision fusion: Through weighted fusion or neural network algorithms, the position information of the radar and the visual characteristics of the camera are integrated to output a more reliable target state (such as "distance 200m, speed 5m/s").

3. Typical application scenarios

Headroom: Measure the distance between the wind turbine blades and the tower.
Intelligent transportation: Radar tracks the speed and location of vehicles in real time, and cameras recognize license plates and traffic violations, and realizes high-precision positioning for red light capture and speed monitoring after fusion.
Security monitoring: Radar detects intrusive targets at night or in haze, triggers the camera to automatically focus and capture high-definition images, improving the real-time and accuracy of perimeter prevention.
Industrial automation: Radar guides the robotic arm to locate the target object, and the camera recognizes the surface features of the object (such as defect detection), realizing the integration of automatic sorting and quality inspection.

Fourth, the technical challenges and optimization directions of the integration solution

Time synchronization error: Latency needs to be reduced by hardware synchronization (e.g., GPS alignment) or software interpolation algorithms.
Data volume processing: Parallel transmission of radar point clouds and 4K video requires optimized bandwidth allocation (e.g., edge computing preprocessing).
Complex scene adaptation: In multi-target intersection and occlusion scenarios, the robustness of the object tracking algorithm (such as multi-sensor joint filtering) needs to be strengthened.