Vector signal analyzer implemented as a synthetic instrument

Abstract

Synthetic Instruments use the substantial signal processing assets of a field programmable gate array (FPGA) to perform the multiple tasks of targeted digital signal processing (DSP) based instruments. The signal conditioning common to many instruments includes analog spectral translation, filtering, and gain control to align the bandwidth and dynamic range of the input signal to the bandwidth and dynamic range capabilities of the A-to-D converter (ADC) which moves the signal from the analog domain to the sampled data domain. Once in the sampled data domain, the signal processing performed by the FPGA includes digital spectral translation, filtering, and gain control to perform its chartered DSP tasks. A common DSP task is spectral analysis from which frequency dependent (i.e., spectral) amplitude and phase is extracted from an input time signal. Another high interest DSP task is vector signal analysis from which time dependent (i.e., temporal) amplitude and phase is extracted from the input time signal. With access to the time varying amplitude-phase profiles of the input signal, the vector signal analyzer can present many of the quality measures of a modulation process. These include estimates of undesired attributes such as modulator distortion, phase noise, clock-jitter, l-Q imbalance, inter-symbol interference, and others. Here, the boundary between synthetic instruments (SI) and software defined radios (SDR) becomes very thin indeed. Essentially this is where the SI is asked to become a smart SDR, performing all the tasks of a DSP radio receiver and reporting small variations between the observed modulated signal parameters and those of an ideal modulated signal. Various quality measures (e.g., the size of errors) have value in qualifying and probing performance boundaries of communication systems.