Real-time spectrum analyzer signal acquisition and storage principle
Real-time spectrum analyzer is an important signal processing tool, widely used in communications, electronic measurement, radar system design and other fields. It realizes real-time monitoring and analysis of broadband signals through efficient signal acquisition and storage mechanism, providing accurate data support for engineers and technicians. The following will elaborate on its signal acquisition and storage principle.
1. Signal Acquisition Principle
The signal acquisition process of the real-time spectrum analyzer begins with the signal input port, which is responsible for receiving external signals. Before the signal is collected, it is usually amplified by a preamplifier to ensure that the signal strength is high enough to be effectively processed by the subsequent circuit. Next, the signal is converted into a digital signal through an analog-to-digital converter (ADC). The accuracy and sampling rate of the ADC have a crucial impact on the quality of signal acquisition. Therefore, real-time spectrum analyzers usually choose high-precision, high-sampling-rate ADCs.
After the signal is digitized by the ADC, it enters the signal processing stage. The main purpose of signal processing is to optimize the collected signal to improve its quality and accuracy. Common signal processing steps include filtering and denoising. Filtering can filter out noise and interference in the signal and retain the effective information in the signal; while denoising is to remove noise in the signal through an algorithm to further improve the clarity and accuracy of the signal.
The working principle of the real-time spectrum analyzer is mainly based on digital signal processing technology and Fourier transform (FFT) algorithm. After the signal is acquired and digitized, the FFT algorithm is used to convert the time domain signal into a frequency domain signal. The FFT algorithm describes the spectral characteristics of the signal by decomposing the signal into a series of sine and cosine waves. This conversion enables the real-time spectrum analyzer to calculate the spectral distribution of the signal in real time and display it in graphical form on the instrument screen.
2. Storage principle
The processed signal will be stored in the memory of the real-time spectrum analyzer for subsequent analysis and processing. The capacity and speed of the memory directly affect the storage and reading efficiency of the signal. Therefore, real-time spectrum analyzers usually choose high-speed and large-capacity memory.
The stored signal format is usually a digital signal, which can be the original signal data or the processed spectrum data. The specific format depends on the application requirements of the real-time spectrum analyzer. The design of the memory must not only ensure the integrity of the signal, but also support fast data access so that the real-time spectrum analyzer can respond and display the analysis results quickly.
In short, the signal acquisition and storage of the real-time spectrum analyzer are the key steps to achieve spectrum analysis, which directly affects the accuracy and reliability of the analysis results. Through high-quality signal acquisition and storage, the real-time spectrum analyzer can better understand the spectral characteristics of the signal and provide reliable data support for subsequent analysis and processing. Therefore, when designing and selecting a real-time spectrum analyzer, it is necessary to pay more attention to the performance and characteristics of signal acquisition and storage to ensure the performance and stability of the instrument.
TFN RMT Series handheld spectrum analyzer supports real-time spectrum analysis function. The maximum bandwidth of real-time spectrum analysis can reach 100MHz, which is at the leading level among similar products. If you are interested in TFN spectrum analyzers, please contact TFN sales team:
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