New Pulse Signal Processing and Analysis Techniques
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Introduction
Pulsed signals are widespread in radar and other EW applications, and they must be accurately measured for manufacturing, design of countermeasures, and threat assessment. However pulse measurements are an especially challenging area for signal analysis due to a combination of factors.
– Wide pulse bandwidth—the result of short pulse duration and fast transitions
– Complex signal environments containing pulses from a number of different sources, often with dramatically different characteristics such as bandwidth, repetition rate and modulation type
– Pulse environments with wide dynamic range in the pulses to be analyzed or created
– Pulses with complex modulation that must be demodulated and decoded or measured
– Pulses that are difficult to detect due to very low duty cycle, intermixing with other signals, and low apparent power level at the analysis point
Fortunately many of the improving signal processing and analog-digital conversion technologies behind the generation of complex pulse environments also enable new techniques for effective pulse analysis. This application note will discuss the best tools and latest developments for different types of pulse analysis, along with display and analysis techniques for various signals and measurement goals. This note will also cover key signal acquisition and processing technologies such as IF and frequency mask triggering, signal capture, and post-processing.
The analysis described here is available in two comprehensive pulsed radar analysis applications:
The N9067C X-Series pulse measurement application is a new internal measurement application for Keysight’s X-Series signal analyzers, providing a high performance one-box measurement solution with bandwidths as wide as 1 GHz that can be operated from the multi-touch front panel interface or through SCPI programming. Option BHQ for the 89600 VSA software adds to general vector signal analysis measurements a broad set of analysis tools and statistical reports of pulse characteristics, operating on both RF/microwave signal analyzer and oscilloscope platforms.
Both of these pulse measurement applications use the same algorithms, providing consistent measurement results and improving measurement confidence. This application note will describe the choice of application software and the associated hardware platforms, along with available triggering and measurement types and displays.
Table of Contents
Pulsed Signals and the Challenge of Signal Acquisition
Choosing RF/microwave hardware for signal analysis
Software for measurements and signal processing
Pulse Analysis Measurement Process and Tools
Functional blocks of pulse measurement
Meeting the Challenges of Complex Pulse Analysis
IF Magnitude trigger
Frequency mask trigger
Time qualified trigger
Oscilloscope holdoff trigger
Dynamic Range and Bandwidth Tradeoffs for Wideband Signals
Capturing Large Numbers of Pulses with Efficient Memory Use
Completely Characterizing Pulse Modulation
Summary
Pulsed Signals and the Challenge of Signal Acquisition
In the past, basic pulse measurements were generally made with swept spectrum analyzers. The intermediate frequency (IF) bandwidth or resolution bandwidth (RBW) of the spectrum analyzer was generally narrower than the effective bandwidth of the pulse, so the spectrum analyzer was used to measure the resulting pulse spectrum. The pulse spectrum could then be used to measure basic signal characteristics such as pulse repetition rate or interval (PRI), duty cycle, power, etc. Spectrum analyzers were also used in more traditional ways to make out-of-band measurements such as spurious and harmonics of pulsed signals.
Though indirect and slightly clumsy, the pulse spectrum approach was adequate for simple pulses and signal environments containing only a single pulse train, and where frequency agility was low or could be inhibited.
Modern systems use much more complex pulses, and many signals or signal environments include a number of different pulses (along with other signals) from one or multiple emitters, as shown in the real-time spectrum measurement of Figure 1.
The combination of complex signals and detailed measurement requirements means that pulse measurements must now be made using digital signal processing (DSP) techniques on digitally sampled signals.
Choosing RF/Microwave hardware for signal analysis
A critical first step is to choose the main measurement hardware platform, a choice that will influence the pulse measurement software that will be discussed later in this note. Rapid increases in signal analyzer bandwidths and improved resolution in digital oscilloscopes are constantly changing the tradeoffs that affect pulse measurements.
Two different RF/microwave hardware measurement platforms—shown in Figure 2—are generally used for this purpose: signal analyzers with a wideband digital IF, and oscilloscopes or digitizers with a sampling rate high enough to directly handle microwave RF/microwave signals at the baseband.
The two hardware front-end approaches are conceptually similar for most pulse measurements. In both cases, the output of the RF/microwave front end (including subsequent processing) is a stream or data file of I/Q samples of the signal or signal environment. The principal architectural difference is the location of the analog to digital conversion (ADC) operations and the type of processing used to focus analysis on the frequency band of interest.
Signal analyzers use a fundamental or harmonic analog mixing process and analog filters to convert RF or microwave signals to an IF section where ADC operations are performed.
Oscilloscopes (and other time-domain samplers such as modular digitizers) sample the RF or microwave signals directly in a baseband fashion, and subsequent downconversion and band-limiting are performed by DSP.
