Radar Signal Learning Model for SAR-Free Target Observation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
SAR image generation processes that filter received signals to reduce data volume can lead to missing information or false detection, affecting the precision and accuracy of object and environmental observations.
Innovation Solution
A learning model is trained using teaching data with received signals and meta-information to output accurate meta-information without filtering, enabling precise observation of target areas using electromagnetic wave reflections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If filtering is applied to received signal to reduce data volume, then data amount is reduced and computational burden is reduced, but information may be lost or false detection occurs affecting observation precision
Solution Approach 1:
The patent applies preliminary action by performing compression processing on the received signal before filtering to extract essential information, then applies filtering to the compressed result. This sequence ensures that critical information is preserved in the compression stage, and filtering subsequently reduces data volume without losing the extracted essential information, thereby resolving the contradiction between data reduction and precision maintenance
Solution Approach 2:
The patent introduces an intermediary element - the compression processing stage - between the received signal and filtering operations. This intermediary extracts and preserves essential information from the raw signal, allowing subsequent filtering to reduce data volume without removing critical observation data, thus maintaining precision while achieving data reduction
2Measurement precision
If SAR image generation is performed to observe target area, then detailed information is obtained, but data transmission amount increases and processing time increases
Solution Approach 1:
The patent extracts only the essential information needed for observation from the complete SAR image generation process. By identifying and extracting key features and metadata directly from the received signal or partial processing results, the system avoids generating full SAR images when complete detail is not necessary, thereby reducing processing time and data transmission requirements while maintaining sufficient observation capability
Solution Approach 2:
The patent applies partial action by performing only the necessary portion of SAR image generation - specifically, generating only the essential information required for the observation task rather than complete high-resolution images. This selective processing approach reduces computational burden and processing time while still providing sufficient detail for effective observation, addressing the contradiction between information detail and processing efficiency
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 learning model allows for high-precision observation of object situations and environments by acquiring meta-information directly from received signals, reducing the need for SAR images and minimizing data transmission requirements.
Implementation Method 1
a received signal that is input to the storage unit is based on a reflected electromagnetic wave which is an electromagnetic wave emitted to a target area by a radar device and then reflected
Data Source
AI summary
The purpose of the present invention is to provide a learning model, a signal processor, a flying object, and a program that enable appropriate observation of the situation of an observed object or the environment around the observed object. The learning model is learned by using teaching data with a first received signal as input, the first received signal being based on a reflected electromagnetic wave that is an electromagnetic wave emitted to a first target area and then reflected, and with first meta-information as output, the first meta-information corresponding to the first received signal and having a predetermined item, so as to input a second received signal based on a reflected electromagnetic wave that is an electromagnetic wave emitted to a second target area and then reflected, and to output second meta-information corresponding to the second received signal and having a predetermined item.