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A threshold activation-based simplified Lv's transform algorithm for transient multi-component linear frequency
The Review of Scientific Instruments
|October 25, 2024
Summary
A new simplified Lv's transform (SLVT) algorithm efficiently analyzes transient signals by only activating upon signal arrival. This method significantly reduces computational load and improves accuracy compared to existing techniques.
Area of Science:
- Digital Signal Processing
- Algorithm Development
- Transient Signal Analysis
Background:
- Modern digital systems generate vast data due to high sampling rates, posing computational challenges.
- Analyzing transient multi-component linear frequency modulation (LFM) signals requires efficient processing methods.
- Existing signal processing techniques can be computationally intensive for sparse transient signals.
Purpose of the Study:
- To propose a computationally efficient algorithm for analyzing transient LFM signals.
- To reduce the computational burden associated with high-sampling-rate digital systems.
- To enhance the accuracy and speed of transient signal analysis.
Main Methods:
- Development of a threshold activation-based simplified Lv's transform (SLVT) algorithm.
- SLVT triggers analysis only upon signal arrival, leveraging signal sparsity.
- Implementation of the stretch keystone transform using the Bluestein chirp-z algorithm, removing redundant computations.
- Comparison with Discrete Fourier Transform (DFT) and other advanced methods.
Main Results:
- SLVT reduces the computational complexity of the original Lv's transform (LVT) by at least 30.8%.
- The algorithm demonstrates superior performance in parameter extraction accuracy, computational complexity, and execution time compared to discrete chirp Fourier transform, fractional Fourier transform, and Radon Wigner transform.
- Field Programmable Gate Array (FPGA) implementation accelerates SLVT computation by a factor of 116 over CPU.
Conclusions:
- The proposed SLVT algorithm offers a significant improvement in efficiency and effectiveness for transient LFM signal analysis.
- SLVT effectively addresses the computational burden of high-sampling-rate systems through sparse signal processing.
- The algorithm's enhanced performance and speed make it suitable for real-time applications and advanced signal processing tasks.
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