Radar Room Perimeter Detection Using Moving and Static Object Cues
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Solution Overview
Problem
Imaging radar systems are costly and not suitable for small form factor devices, making it difficult to accurately determine the perimeter of a physical space without using cost-prohibitive antennas and complex cable routing.
Innovation Solution
Utilizing an array of radar sensors with receivers arranged in a plane to sense depth via radar signal modulation, combined with processors to detect reflector points and determine the perimeter of a physical space based on energy level comparisons and geometric properties of moving and static objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If imaging radar is used to scan a room and produce precise point cloud measurements, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The imaging radar system is segmented into multiple independent low-cost radar sensors distributed throughout the space. Each sensor captures partial data, and the system reconstructs the complete point cloud by integrating measurements from multiple sensors, eliminating the need for complex single-point imaging radar hardware
Solution Approach 2:
Instead of using a single complex imaging radar, the system uses multiple copies of simple, low-cost radar sensors. These sensors are placed at different locations to collectively capture the same spatial information that a single imaging radar would provide, reducing both device complexity and cost while maintaining measurement precision
2Measurement precision
If imaging radar with precise antennas is used, then measurement precision is improved, but ease of manufacture deteriorates
Solution Approach 1:
The system divides the measurement task into multiple segments performed by distributed low-cost radar sensors. Each sensor is simple to manufacture and install, requiring minimal cable routing compared to a single complex imaging radar system, while collectively achieving precise room dimension measurements
Solution Approach 2:
The system replaces expensive, difficult-to-manufacture imaging radar components with multiple inexpensive radar sensors. These simple sensors are easy to manufacture and install, sacrificing the need for precision engineering of individual components while maintaining overall system accuracy through distributed measurement and data fusion
3Reliability
If imaging radar is deployed, then reliability of perimeter identification is improved, but device complexity increases
Solution Approach 1:
The perimeter identification function is segmented across multiple independent radar sensors. Each sensor contributes to detecting reflector points and identifying corners, with the system achieving reliable perimeter identification through integration of data from multiple simple sensors rather than relying on a single complex imaging radar system
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
Enables accurate estimation of a physical space's perimeter using low-cost radar sensors, suitable for small devices, by identifying convex corners, reflective objects, and distinguishing between walls and ceilings/floors, even in noisy environments.
Implementation Method 1
a radar sensor to sense points in a scene that are reflective of radar signals transmitted by the radar sensor
Implementation Method 2
points in a scene that are reflective of radar signals transmitted by the radar sensor
Data Source
AI summary
An example technique may include receiving radar sensor data from a radar sensor including an array of receivers arranged in a plane and configured to sense depth. The technique may also include detecting a first moving object and a second moving object present in a scene using the radar sensor data. The technique may also include extracting measurements from the radar sensor data for at least one static object in the scene. The technique may also include detecting extents of the first moving object and the second moving object based at least in part on a portion of the measurements and the radar sensor data. The technique may also include determining a physical location of the static object using the measurements and the extents of the first moving object and the second moving object.