Handheld spectrum analyzers track elusive RF signals

Handheld spectrum analyzers track elusive RF signals

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By eeNews Europe

With unique DPX technology along with built-in mapping and signal classification features in a compact, ruggedized package, the instruments are designed to allow spectrum regulators to efficiently manage and monitor spectrum in the field and hunt down elusive signals and interferers. By color-coding events based on the rate of occurrence over thousands of spectrum captures per second, DPX technology provides insight into transients as brief as 125 μs with 100 percent probability of intercept.

This offers a tremendous improvement over conventional swept analysis techniques. The H500 and SA2500 with 10kHz-6.2GHz frequency coverage, 20 MHz real time bandwidth and -163 dBm Displayed Average Noise Level (DANL) match the performance of many benchtop spectrum analyzers. The new models feature intuitive user controls for quick and simple classification and location of both analog and digital RF transmissions. The user interface is designed specifically for enhanced productivity in the field including a touch screen for easy navigation. While other solutions may require offline GPS and mapping software, the H500 and SA2500 include integrated GPS and mapping tools to allow more efficient interference location capability. Fully ruggedized to withstand shock and moisture, the H500 and SA2500 weigh in at just over 5.5kg and feature the industry’s only hot swap power system. Battery life is rated at five hours of continuous spectrum scanning.

In addition to live RF, the waveform image processor also provides an intensity-graded persistence display that holds anomalies until the eye can see them to show the history of occurrence for dynamic signals and immediate feedback on signal variations over time. This provides engineers the ability to rapidly see on screen both transients and signals that ordinarily could not be seen, either because they are masked by other signals or could only be deduced after time consuming offline analysis.

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