T-Shaped Phased Array Radar for Drone Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current active electronically scanned array (AESA) radar systems are unsuitable for detecting micro-flying drones due to their large size, high cost, and complexity, which makes them inefficient for civilian applications, especially for targets with small radar cross-sections, low flying speeds, and arbitrary trajectories.
Innovation Solution
A two-dimensional sparse orthogonal linear phased array radar system with subarrays arranged in a T-shaped configuration, where data from horizontal and vertical subarrays is combined and processed to generate beamformed data indicating target azimuth and elevation information, reducing manufacturing costs and signal processing complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fully populated planar array configuration is adopted, then target detection capability is improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The radar array is divided into multiple subarrays, each responsible for detecting targets in specific spatial regions. This segmentation allows the system to achieve comprehensive target detection coverage while reducing the processing complexity for each individual subarray, as each subarray only needs to process signals from its designated region rather than the entire array.
Solution Approach 2:
The patent introduces a hierarchical processing structure that adds a dimensional layer to signal processing. Instead of processing all array elements simultaneously in a single plane, the system processes signals from multiple subarrays at different hierarchical levels, transforming the two-dimensional array processing into a multi-dimensional processing approach that reduces overall complexity.
2Reliability
If a fully populated planar array configuration is adopted, then target detection capability is improved, but manufacturing cost increases
Solution Approach 1:
By segmenting the array into multiple subarrays, the patent reduces the number of antenna elements required in each subarray while maintaining overall detection capability. This segmentation strategy lowers the manufacturing cost for each subarray module, making the overall system more cost-effective to produce and deploy.
Solution Approach 2:
The patent employs partial action by having each subarray process only the signals from its designated spatial region rather than processing all array elements. This partial processing approach reduces the computational resources and manufacturing complexity required for each subarray while still achieving comprehensive target detection through the combined output of all subarrays.
3Reliability
If a fully populated planar array configuration is adopted, then target detection capability is improved, but power consumption increases
Solution Approach 1:
The array segmentation allows each subarray to operate independently with reduced power consumption. Since each subarray processes only signals from its designated region, the power consumption per subarray is significantly reduced compared to a fully populated array processing all signals simultaneously. The cumulative power consumption of multiple low-power subarrays is less than that of a single high-power fully populated array.
Solution Approach 2:
The partial action principle is applied by having each subarray process only the necessary signals from its spatial region rather than processing all array elements. This reduces the computational load and associated power consumption for each subarray, making the overall system more energy-efficient while maintaining target detection capability through the combined output of all subarrays.
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
The proposed system effectively detects and positions targets in three-dimensional space with high accuracy, reducing costs and complexity while efficiently handling small radar cross-sections and arbitrary trajectories, making it suitable for civilian drone surveillance.
Implementation Method 1
generate first beamformed data indicating target azimuth information by applying beamforming to the combined set of data
Data Source
AI summary
A radar system includes a first subarray, a second subarray and a third subarray. The first subarray includes a plurality of first antennas arranged along a first direction. The second subarray includes a plurality of second antennas arranged along the first direction. The third subarray includes a plurality of third antennas arranged along a second direction orthogonal to the first direction. The third subarray is configured to combine a first set of data received from the first subarray and a second set of data received from the second subarray into a combined set of data, generate first beamformed data indicating target azimuth information by applying beamforming to the combined set of data, and generate second beamformed data indicating target elevation information according to a plurality of input signals received by the third antennas.