Handheld Radar and Image Sensor Fusion for 3D Object Positioning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for 3D object positioning on handheld devices, such as radar systems with single directional antennas and stereo image analysis, face challenges in complex environments with many similar objects or featureless images, leading to inaccurate position estimation.
Innovation Solution
A handheld device equipped with a radar sensor and an image sensor that emits detection waves, captures images, and uses waveform signatures in both time and frequency domains to determine object types and positions, combining these with image-based positions through mapping to achieve accurate 3D space positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar beam scanning with array antenna is used to obtain 3D position, then positioning capability is improved, but device complexity increases making it hard to implement on handheld devices
Solution Approach 1:
The patent combines radar sensor and image sensor into a unified handheld device system, where the radar sensor uses a single directional antenna and the image sensor captures visual information. By merging these two sensing modalities, the system achieves 3D positioning capability without requiring complex array antenna beam scanning, thus reducing device complexity while maintaining positioning accuracy.
2Device complexity
If stereo image analysis is used to estimate 3D space, then implementation on handheld devices is simplified, but accuracy deteriorates in complex environments with many similar objects or featureless images
Solution Approach 1:
The patent introduces radar sensor data as an intermediary to assist and correct image-based position estimation. The radar sensor provides accurate distance and position information that serves as a reference to guide image processing, enabling the system to accurately identify and position objects even in complex environments with many similar objects or featureless images, thereby improving measurement precision while maintaining implementation simplicity.
3Device complexity
If single sensor type is used for object detection, then device simplicity is maintained, but detection accuracy and reliability are insufficient in complex environments
Solution Approach 1:
The patent merges radar sensor and image sensor into a complementary multi-sensor system. The radar sensor detects objects based on electromagnetic wave reflection, providing reliable distance and position data, while the image sensor captures visual features for object identification. By combining these different sensing modalities, the system achieves high detection accuracy and reliability in complex environments while maintaining relatively simple device architecture.
Solution Approach 2:
The patent implements feedback mechanisms where radar detection results guide image processing and object identification, and vice versa. The radar provides initial object location information that focuses image analysis, while image data refines object identification and classification. This mutual feedback between sensors enhances detection reliability without significantly increasing device complexity.
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 collaborative approach enables complete and accurate 3D space positioning of objects, improving accuracy in complex environments and enhancing 3D image applications like virtual reality and object refocusing.
Implementation Method 1
The radar sensor emits a detection wave, and receives at least one reflected wave generated by at least one object by reflecting the detection wave
Implementation Method 2
The image sensor captures an image. The image includes a subset of the at least one object
Data Source
AI summary
A handheld device, an object positioning method thereof and a computer-readable recording medium are provided. The handheld device includes a radar sensor, an image sensor and a control unit. The radar sensor emits a detection wave, and receives a reflected wave generated by an object by reflecting the detection wave. Each object generates one of the reflected waves. The image sensor captures an image. The image includes a subset of the objects. The control unit extracts a waveform signature of each reflected wave, recognizes the waveform signature in a time domain and a frequency domain to determine a first type of each object, obtains a first position of the object according to the reflected wave, obtains a second type and a second position of each object according to the first image, and performs object mapping to combine or compare the first position and the second position of the object.