Beam Steering Radar Decision Network for Object Detection
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Solution Overview
Problem
Current autonomous driving technologies face challenges in accurately detecting and classifying objects in real-time across varying environmental conditions, with existing sensors like cameras and lidars being limited by adverse weather and range constraints, while radars offer all-weather capabilities but struggle with detailed object recognition.
Innovation Solution
A beam steering radar system integrated with a decision network and sensor fusion module, utilizing a convolutional neural network for object detection and beam steering antenna control, enabling dynamic beam steering and enhanced object recognition capabilities across a 360° field of view, combining radar, camera, and lidar data for comprehensive object detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radar is used for object detection, then all-weather detection capability is improved, but object recognition precision deteriorates
Solution Approach 1:
The patent combines radar, camera, and lidar sensors into an integrated sensor system that fuses data from multiple sources. This merging allows the system to leverage radar's all-weather detection capability while compensating for its limited recognition precision using complementary data from cameras and lidars, achieving both reliability and measurement precision simultaneously.
Solution Approach 2:
The patent introduces a decision network as an intermediary component that processes radar data and determines whether additional sensing is needed. This intermediary analyzes radar detections and decides when to trigger supplementary sensing from other modalities, enabling the system to maintain all-weather operation while improving recognition precision through selective multi-sensor fusion.
2Productivity
If beam steering antenna is used, then object detection speed is improved, but system complexity increases
Solution Approach 1:
The patent implements a dynamic beam steering antenna system that can electronically redirect radar beams without mechanical movement. This dynamic capability allows the system to rapidly scan multiple directions and track objects in real-time, significantly improving detection speed. The electronic steering reduces mechanical complexity compared to traditional rotating antenna systems while maintaining high productivity.
Solution Approach 2:
The patent replaces mechanical rotation of the antenna with electronic beam steering technology. Instead of physically rotating the antenna to scan different directions, the system uses electronic phase control to redirect beams dynamically. This substitution eliminates mechanical wear and increases detection speed while reducing overall system complexity by removing moving parts.
3Measurement precision
If multiple sensors are integrated, then object detection accuracy is improved, but device complexity increases
Solution Approach 1:
The patent creates a universal sensor fusion platform that handles radar, camera, and lidar data through a common processing architecture. This multi-functional system uses a single decision network and sensor fusion module to process diverse sensor inputs, achieving high detection accuracy across all sensor types while reducing overall complexity through standardized processing pathways rather than separate dedicated systems for each sensor.
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 system achieves human-like interpretation of the environment with accurate object detection and classification over long ranges, optimizing sensor performance in all weather conditions and enhancing the possibility of fully self-driving cars by leveraging radar's strengths and integrating with other sensors.
Implementation Method 1
a beam steering radar system in an autonomous vehicle is used to detect and identify objects
Data Source
AI summary
Examples disclosed herein relate to a radar system in an autonomous vehicle. The radar system has a radar module including at least one beam steering antenna and an antenna controller. The radar system also includes a perception module having an object detection module to detect objects in a path and surrounding environment of the autonomous vehicle, and a decision network to determine a control action for the antenna controller to perform based on the detected objects and a control policy.