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A spectrum analyzer is a powerful tool used to analyze the spectral structure of electrical signals. It helps in studying signal distortion, modulation, spectral purity, stability, and frequency intermodulation distortion. This versatile electronic measuring instrument can also be referred to as a frequency domain oscilloscope, tracking oscilloscope, analytical oscilloscope, harmonic analyzer, frequency characteristic analyzer, or Fourier analyzer.
Modern spectrum analyzers are capable of displaying analysis results either analog or digitally. They can process electrical signals across a wide range of radio frequencies, from very low frequencies up to sub-millimeter bands below 1 Hz. When equipped with digital circuits and microprocessors, these instruments offer storage and calculation capabilities. With standard interfaces, they can easily integrate into automatic test systems.
Spectrum analyzers are often based on Fast Fourier Transform (FFT) technology. This allows them to decompose a measured signal into discrete frequency components using Fourier operations, achieving results similar to traditional analyzers. The new generation of analyzers uses a digital method, where the input signal is directly sampled by an analog-to-digital converter (ADC), and then processed via FFT to generate a spectral distribution map.
To ensure good linearity and high resolution, the ADC sampling rate must be at least twice the highest frequency of the input signal. For example, a real-time spectrum analyzer with an upper frequency limit of 100 MHz requires an ADC with a sampling rate of 200 MS/s. Current ADCs may have 8-bit resolution with a sampling rate of 4 GS/s or 12-bit resolution with a sampling rate of 800 MS/s, allowing the instrument to reach a bandwidth of up to 2 GHz. To extend the frequency range, a downconverter can be added before the ADC, and a digitally tuned local oscillator can be used, enabling operation at frequencies below a few GHz.
The performance of the FFT is determined by the number of sampling points and the sampling rate. For instance, if a signal is sampled at 1024 points with a sampling rate of 100 kS/s, the maximum input frequency is 50 kHz, and the frequency resolution is 50 Hz. Increasing the number of sampling points to 2048 improves the resolution to 25 Hz. While higher sampling rates allow for higher input frequencies, more sampling points increase the FFT processing time.
The FFT operation time grows logarithmically with both the sampling rate and the number of points. For high-speed, high-resolution applications, fast FFT hardware or specialized digital signal processor (DSP) chips are used. For example, processing 1024 points at 10 MHz takes about 80 μs, but at 10 kHz it increases to 64 ms, and at 1 kHz it reaches 640 ms. If the processing time exceeds 200 ms, the display response becomes sluggish, making it unsuitable for real-time observation. To improve this, the number of sampling points can be reduced to keep the operation time under 200 ms.
Overall, a spectrum analyzer is an essential tool in signal analysis, providing detailed insights into the frequency domain characteristics of signals, and plays a crucial role in modern electronics and communication systems.