Possible alternatives to overcoming speed limitations using synthetic instruments signal analysis architecture

Abstract

Signal Analyzers have been widely used in automatic test equipment (ATE) since the first computer controlled Spectrum analyzer introduced by Hewlett Packard (now Agilent) back in 1978. These signal analyzers are widely used to find signals in the frequency domain whether wanted or unwanted (spurious signals). One of the largest issues with signal analyzers are their ability to create additional signals, internally, which pretend to be real signals on their display. This may be misleading and cause the operator to spend hours, if not days, troubleshooting a problem with their device. Because of these unintentional signals, instrument manufacturers have developed a number of architectures that would minimize the unwanted signals without suppressing the signals that are the target of the measurement. With the advent of the synthetic instrument (SI) architecture, signal analyzers have taken advantage of new Analog-to-Digital Converters (ADC) and faster computers (Signal Processors) to identify signals, faster and with greater fidelity. However, even with these latest SI instruments they still take longer to measure small, unknown, spurious signals over wide spans and older, traditional, spectrum analyzers. This would not be a problem if it were not the longest measurement in the test suite. Low level spur searched can take from milliseconds to several minutes to even hours if a wide span needs to be searched with traditional spectrum analyzers. With an SI signal it could be 2 to 20 time slower making it unusable in an ATE environment. This paper will explore different signal analyzer architectures and the benefits and limitations of each. This paper will also explore how a signal analyzer processes a measurement and how engineers can deduce the time of measuring low levels spurs in each of these processes. And finally, this paper will show potential ways a synthetic architecture can improve the spur searching capability over the traditional spectrum analyzers yielding improved productivity in ATE applications.