Small Object Detection Using Multi-Radar Mesh Networks
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Solution Overview
Problem
Existing communication networks face challenges in detecting and accurately locating small moving objects, especially in dynamic and hostile RF environments, due to interference, limited range, and susceptibility to noise.
Innovation Solution
The use of multiple radars with directional antennas, such as phased array antennas, operating in a mesh network with millimeter wave radios, allows for improved detection and localization of small moving objects by enhancing range and angular resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single radar is used for detection, then the device complexity is low, but the measurement precision and detection accuracy are insufficient
Solution Approach 1:
The system divides the detection task across multiple independent radar units, each contributing to the overall detection accuracy. By segmenting the detection function across multiple sensors rather than relying on a single complex radar, the system achieves higher measurement precision while maintaining manageable device complexity through modular architecture.
Solution Approach 2:
Multiple radar detections are merged and combined to produce a unified, more accurate object detection and localization result. The system integrates data from multiple radar units, combining their individual measurements to achieve superior detection accuracy that exceeds what any single radar could provide alone.
2Measurement precision
If multiple radars are deployed to improve detection accuracy, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
Each radar unit in the network is designed to perform multiple functions: detection, localization, and data sharing with other network nodes. This multi-functionality allows the system to achieve high location accuracy through multiple radars while reducing overall complexity, as each unit is a self-contained, versatile component rather than a specialized single-function device.
Solution Approach 2:
The system transitions from single-radar two-dimensional detection to multi-radar three-dimensional localization. By adding the spatial dimension of multiple radar positions, the system achieves superior location accuracy in 3D space, transforming the detection problem from a single-point measurement to a multi-point spatial intersection that naturally improves precision.
3Length of stationary object
If radar power is increased to extend detection range, then the detection range improves, but the use of energy increases
Solution Approach 1:
The detection range extension is achieved by segmenting the monitoring task across multiple radar nodes distributed in space. Each radar operates at moderate power levels, but their collective coverage area extends the overall detection range without requiring any single radar to consume excessive energy, dividing the energy burden across multiple units.
Solution Approach 2:
The mesh network acts as an intermediary system that relays and shares detection data between radar nodes. This allows each radar to operate at lower power levels while still achieving extended effective detection range through networked cooperation, where the intermediary network infrastructure enables range extension without direct proportional increases in individual power consumption.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly improves the accuracy and reliability of detecting and tracking small moving objects, reducing interference and noise effects, and enabling more precise location determination in dynamic environments.
Implementation Method 1
Methods and systems for flying small object detection using radar
Data Source
AI summary
Systems and methods are provided for small object detection using radar. An example arrangement may include a plurality of radars, and at least one processing node that includes one or more processing circuits. The plurality of radars are physically separated. The plurality of radars is arranged such that coverage areas of the plurality of radars overlap, at least partially. The plurality of radars is configured to utilize differentiation techniques for differentiating each of the plurality of radars. The plurality of radars is configured to share detection related data obtained or generated by each of the plurality of radars based on detection of objects within the coverage areas. The one or more processing circuits are configured to process the shared detection related data and information relating to positions of the radars, to detect and/or track one or more objects.