Radar Signal Processing Device for Real-Time Local Characteristic Analysis
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Solution Overview
Problem
Conventional radar signal processing devices face challenges in obtaining local characteristics of small regions in real-time and with low computation, especially during wide-area or high-speed observations, due to the complexity and cost associated with existing methods.
Innovation Solution
A radar signal processing device that includes a signal transmitting and receiving unit, a signal cutting-out unit, a power spectrum calculating unit, and a power spectrum reconstructing unit, which cuts out reflected signals by a specific length, calculates multiple power spectra, and reconstructs power spectra to enhance the contribution rate in a set region, allowing for real-time and low-computation local characteristic analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the pulse width is reduced to decrease the scattering volume for high resolution observation, then the spatial resolution is improved, but the transmission energy decreases and the observed range is reduced
Solution Approach 1:
The patent divides the received signal into multiple overlapping segments (first signal segment and second signal segment) from different scattering volumes. By processing these segmented signals separately and combining their power spectra, the system achieves high spatial resolution without requiring a single short pulse, thus maintaining transmission energy.
Solution Approach 2:
The patent transitions from temporal resolution (pulse width) to spectral domain processing (power spectrum reconstruction). By performing Fast Fourier Transform on segmented signals and reconstructing power spectra in the frequency domain, the system achieves spatial resolution enhancement without reducing the temporal pulse width, thereby preserving transmission energy.
2Measurement precision
If pulse compression with band widening (phase modulation or frequency modulation) is used to achieve high resolution, then the spatial resolution is improved, but the device configuration becomes complex and cost increases
Solution Approach 1:
The patent extracts only the necessary processing steps (segmentation, Fast Fourier Transform, power spectrum reconstruction) from the complex pulse compression system. By taking out the essential high-resolution achieving steps and implementing them through simple signal segmentation and spectral analysis, the system avoids the need for complex modulation devices while maintaining spatial resolution.
Solution Approach 2:
The patent uses computationally simple operations (segmentation and power spectrum calculation) instead of expensive hardware modulation components. The processing relies on basic mathematical operations that can be implemented with low-cost computational resources, replacing complex physical modulation systems.
3Measurement precision
If conventional optimization techniques with inverse matrix computation or iterative computation are used to process oversampled signals, then local characteristics are obtained, but the computation amount increases and real-time processing becomes difficult
Solution Approach 1:
The patent extracts and uses only the power spectrum information from each signal segment, discarding the need for complex inverse matrix computations or iterative optimizations. By focusing on the essential spectral characteristics and using direct power spectrum reconstruction, the system achieves local characteristic detection with minimal computation.
Solution Approach 2:
The patent replaces computationally expensive operations (inverse matrix computation, iterative optimization) with simple, fast operations (segmentation, Fast Fourier Transform, power spectrum calculation). These lightweight computational operations can be executed rapidly, enabling real-time processing while maintaining detection accuracy.
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 the grasping of local characteristics with a low amount of computation and in real-time, maintaining the observed range and avoiding significant changes in device configuration, thus overcoming the limitations of existing methods.
Implementation Method 1
radiating a transmission signal made of an electromagnetic wave or a sound wave into air
Implementation Method 2
receiving a reflected signal, the reflected signal being the transmission signal reflected by a target in the air
Implementation Method 3
calculating a plurality of power spectra from the signals cut out by the signal cutting-out unit
Data Source
Figure 1
Figure 2
Figure 3A~3D
AI summary
A signal cutting-out unit (31) cuts out a signal reflected from a target by a specific length while the cut-out signals are overlapped by a set length. A power spectrum calculating unit (32) calculates a plurality of power spectra from output signals from the signal cutting-out unit (31). A power spectrum reconstructing unit (33) performs power spectrum reconstruction by changing a ratio or contribution rate of power spectrum components in a set region, using the plurality of power spectra. A spectral moment calculating unit (34) calculates a spectral moment from a power spectrum reconstructed by the power spectrum reconstructing unit (33).