A signal analyzer is an electronic device that measures the electrical signals sent and received by electrical components. Two basic types of signal analyzers are spectrum analyzers (SA) and vector signal analyzers (VSA). Spectrum analyzers are used to measure basic signal properties of basic signals. These properties include frequency, magnitude and amplitude. Vector signal analyzers are used to perform more complex measurements, such as modulation, of more dynamic types of signals. Signals input into a signal analyzer are downconverted into an intermediate frequency for easier analysis and are digitized to undergo complex algorithmic calculations.

Averaging is a technique employed by signal analyzers to account for the noise that accompanies many types of electrical signals. Two types of averaging may be performed by signal analyzers. RMS averaging is used to determine signal magnitude but it cannot improve the signal-to-noise ratio. Linear averaging is a technique that uses several measurements over a period of time to improve the signal-to-noise ratio of the measurements.

Band selectable analysis (BSA) is a feature of most signal analyzers that allows a user to set minimum and maximum frequencies of signals to be measured. Signals outside the selected frequency range are filtered out of the measurements. BSA provides signal analysis at a much higher resolution than is possible with all frequencies in the spectrum.

Coherence is a measurement of the power response of a signal, which is the measured output of reference power in relation to the input. This measurement helps to eliminate interference in the signal measurements caused by outside forces, such as machine vibration or other electrical signals.

The displayed average noise level (DANL) of a signal analyzer represents the sensitivity of the analyzer. DANL is the noise floor and includes internally generated noise. Signals lower than the DANL cannot be measured by the signal analyzer.

The dynamic range of a signal analyzer is the ratio of the maximum signal amplitude that can be measured to the minimum measurable signal amplitude. Dynamic range is expressed as a single value, which is the difference between the maximum and minimum amplitudes.

A dynamic signal analyzer is capable of measuring a wide range of electrical signals through a wide range of filters. Measurements can be made by dynamic signal analyzers in all three domains: the time domain, the frequency domain and the modal domain. Dynamic signal analyzers are also known as FFT analyzers because their measurements are based on the Fast Fourier Transform algorithm.

Fast Fourier transform (FFT) is an algorithm developed to efficiently convert electrical signal measurements from the time domain to the frequency domain. Because of the complexity of the calculations, the FFT algorithm can only be practically applied in signal analyzers with a digital microprocessor.

The frequency domain is one of the three domains, or perspectives, through which electrical signals can be analyzed. A set of signals is measured in the time domain by a signal analyzer and converted to the frequency domain by applying the FFT algorithm. Converting a signal to the frequency domain involves breaking the signal down into individual sine waves.

Frequency response is a characteristic of a network, as opposed to the characteristic of an electrical signal. It is defined as the ratio of the magnitude and phase of a networkâ€™s input signal to the output signal that is produced.

The modal domain is one of the three perspectives through which electrical signals are analyzed. The modal domain measures the characteristics of a network or another mechanical structure that creates an electrical signal. Measurements of the signal in the time domain and frequency domain each correspond to a specific vibration mode of a network. All of the characteristics of a signal are included in its total set of vibration modes. Measurements in the modal domain are measurements of the state of the network as a specific signal traverses through it.

A network analyzer is a type of signal analyzer that is optimized to measure a wide range of communications signals between two or more electronic components over a network. This optimization ensures accurate measurements of amplitude and phase.

FFT computations take time. The time record of measurements taken by a signal analyzer varies by the frequency span of the analyzer. The wider the frequency span, the shorter the time record will be. If the frequency span is sufficiently increased, the time record will equal the FFT computational time. The frequency span at this point is the realtime bandwidth.

Demodulation occurs when the signal encoded with information in a broadcast wave is stripped from the accompanying carrier wave. Demodulation is part of the regular process of a radio receiver, but it can also be performed by a signal analyzer.

A spectrum analyzer is a type of signal analyzer that is designed to measure detailed characteristics of electrical signals. This is accomplished by filtering out distortion and signal interference from outside sources. Spectrum analyzers are available in two basic versions: parallel-filter spectrum analyzers and swept spectrum analyzers.

A swept-based analyzer is a signal analyzer that collects electronic signals through a single filter that sweeps through a frequency range. In contrast, a parallel-filter analyzer covers a frequency range by using multiple overlapping filters tuned to different frequencies.

Also known as IP3 or TOI, third-order intercept is a method for measuring nonlinear systems. TOI is based on harmonics and the products of intermodulation between the fundamental signal and a secondary signal.

The time domain is one of the three domains, or perspectives, through which electrical signals can be measured and analyzed. The time domain in signal analysis is a set of measured signals in relation to when the measurements were recorded. The time domain is the basic domain through which signals are measured. Signal measurements in the other two domains must be converted from the time domain.

A vector signal analyzer is a type of signal analyzer designed to measure the magnitude and phase of signals. This process is known as vector detection. Vector signal analyzers are capable of measuring both RF and microwave signals, and they include the ability to convert signals into the modal domain.

One of the reasons FFT is so fast and efficient is because it assumes that a set of measurements is indefinitely repeated. This causes a signal analyzer error called leakage when reading sine waves. The error affects the readings on the ends of the time record. To correct this error, a dynamic signal analyzer multiplies the record by a function that concentrates on the reading at the center of the time stamp and away from the ends. This correction is called windowing.