Target Estimation System Using Segmented Signal ID and CSI Units
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing number-of-person estimation methods using signal ID information or CSI information face limitations in achieving higher accuracy, as each estimation is executed independently without comprehensive integration of different information types.
Innovation Solution
A number-of-target estimation system that combines a first estimation unit for initial number estimation using radio or image information, a wireless propagation path acquisition unit for acquiring CSI, and a second machine learning-based estimation unit for final estimation, which selects appropriate models based on the initial estimation results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If estimation is executed independently using only signal ID information or only CSI information, then the system complexity is reduced, but the estimation accuracy cannot be further improved
Solution Approach 1:
The estimation system is segmented into multiple independent estimation units, each processing different information types (signal ID information and CSI information separately). This allows each unit to operate independently with reduced complexity while the final accuracy is improved through integration of results from multiple units.
Solution Approach 2:
The patent merges the results from multiple independent estimation units by integrating signal ID information and CSI information through a unified estimation process. This combining approach achieves higher estimation accuracy than individual methods while managing system complexity through modular architecture.
2Measurement precision
If multiple information types are integrated for estimation, then the estimation accuracy is improved, but the system complexity increases
Solution Approach 1:
The system divides the complex task of integrating multiple information types into separate estimation units, each handling specific information (signal ID or CSI). This segmentation reduces the complexity burden on any single component while maintaining the benefits of multi-information integration through coordinated operation.
Solution Approach 2:
The estimation system is designed with multi-functional capability to process both signal ID information and CSI information through unified estimation units. This universality allows the system to handle multiple information types without requiring completely separate processing pipelines, thereby managing complexity while achieving high accuracy.
Data Source
AI summary
According to one embodiment, an estimation system tentatively estimating the number of targets existing in a first area, based on radio information or image information excluding wireless propagation path information, which is related to the first area, receiving a radio signal transmitted from a radio in the first area and acquiring wireless propagation path information from the received signal, and performing a final number-of-target estimation by machine learning, using a result of the tentative estimation and the acquired wireless propagation path information as input information. The estimation system selects models to be used for the estimation of the machine learning, based on a result of the tentative estimation, when performing the final number-of-target estimation.