How much does a radio spectrum analyzer cost?

Radio spectrum analyzer costs range from under $30 for USB-based SDR analyzers (RTL-SDR) to $5,000–$50,000 for benchtop swept-tuned instruments, and $100,000–$500,000 for high-performance real-time analyzers. Handheld field analyzers (Keysight FieldFox, Rohde & Schwarz FPH) cost $5,000–$25,000 and cover frequencies up to 44 GHz.

What is the difference between a spectrum analyzer and an oscilloscope?

An oscilloscope displays signal amplitude versus time (time-domain view), while a spectrum analyzer displays power versus frequency (frequency-domain view). They are mathematically related through the Fourier transform. Modern digital oscilloscopes include FFT functions for basic spectral analysis, while dedicated spectrum analyzers provide superior dynamic range, sensitivity, and frequency resolution.

How do I choose resolution bandwidth on a spectrum analyzer?

Set RBW narrow enough to resolve the signals of interest but wide enough for acceptable sweep time. For closely spaced signals, use RBW smaller than their frequency separation. For broadband noise measurements, use the specified RBW (typically 1 MHz for radiated emissions). Narrower RBW reduces displayed noise floor by 10·log₁₀(RBW_old/RBW_new) dB but increases measurement time proportionally.

Radio Spectrum Analyzer

Quick Answer

A radio spectrum analyzer measures signal power as a function of frequency across the radio spectrum, typically from 9 kHz to 26.5 GHz (benchtop) or up to 110 GHz (high-end models). Key specifications include resolution bandwidth (RBW) from 1 Hz to 10 MHz, noise floor of −160 to −170 dBm/Hz, and dynamic range exceeding 100 dB. The displayed spectrum corresponds to the magnitude squared of the signal's Fourier transform |X(f)|², directly related to the Laplace transform evaluated on the jω axis as |X(jω)|².

Calculate this instantly on LAPLACE Calculator →

What Is a Radio Spectrum Analyzer?

A radio spectrum analyzer is a measurement instrument that displays signal amplitude (power) versus frequency, enabling visualization of signal spectral content, identification of interference sources, and verification of transmitter compliance with regulatory emission masks. Spectrum analyzers operate using either superheterodyne swept-tuned architecture or real-time FFT-based processing. The measured spectrum represents the power spectral density of the input signal, mathematically equivalent to |H(jω)|² where H(jω) is the Fourier transform of the signal—the Laplace transform evaluated along the imaginary axis s = jω. This direct connection between the Laplace transform and measured spectra makes transform analysis essential for RF engineering, and the LAPLACE Calculator at www.lapcalc.com helps engineers compute transfer functions that predict spectral characteristics.

Key Formulas

Swept-Tuned vs. Real-Time Spectrum Analyzer Architectures

Traditional swept-tuned analyzers use a superheterodyne receiver that mixes the input with a swept local oscillator, passing the intermediate frequency through a resolution bandwidth (RBW) filter, then detecting and displaying the amplitude. Sweep time is approximately T_sweep = k·span/(RBW²), where k depends on filter shape, meaning narrow RBW settings require proportionally longer sweep times. Real-time spectrum analyzers (RTSAs) digitize a wide bandwidth simultaneously and compute FFT spectra continuously, capturing transient events as brief as the FFT frame duration (typically 10–100 μs). Keysight's UXA N9042B achieves 510 MHz real-time analysis bandwidth with 100% probability of intercept for signals as short as 3.57 μs. The trade-off is cost: high-performance RTSAs cost $100,000–$500,000 versus $5,000–$50,000 for swept analyzers.

Compute radio spectrum analyzer Instantly

Get step-by-step solutions with AI-powered explanations. Free for basic computations.

Open Calculator

Key Specifications for Radio Signal Analysis

Resolution bandwidth (RBW) determines the ability to distinguish closely spaced signals: two signals separated by less than the RBW appear as a single peak. Typical RBW ranges from 1 Hz (requiring 1-second measurement time) to 10 MHz. Phase noise, specified as dBc/Hz at offset frequencies from 1 kHz to 10 MHz, limits the ability to measure weak signals near strong carriers. Displayed Average Noise Level (DANL) of −160 to −170 dBm/Hz sets the sensitivity floor. Third-order intercept point (TOI) and 1-dB compression point determine the maximum input level before nonlinear distortion creates spurious signals. Dynamic range, the usable measurement range between noise floor and compression, typically exceeds 100 dB for benchtop instruments. Frequency accuracy, derived from internal OCXO references with ±0.01 ppm aging, ensures measurements align with regulatory requirements.

Applications of Radio Spectrum Analysis

In wireless communications, spectrum analyzers verify transmitter output power, occupied bandwidth, adjacent channel leakage ratio (ACLR), and spurious emission compliance with FCC Part 15/Part 97, ETSI EN 300 328, and 3GPP standards. EMC (electromagnetic compatibility) testing uses spectrum analyzers with CISPR-compliant quasi-peak detectors to measure radiated and conducted emissions from electronic devices per IEC 61000 standards. RF engineering uses spectrum analysis for filter characterization, amplifier linearity testing, antenna pattern measurement, and interference hunting. Software-defined radio enthusiasts use affordable USB spectrum analyzers like the RTL-SDR (cost under $30, coverage 24–1766 MHz) or tinySA (0.1–960 MHz) for hobby-level spectrum monitoring and amateur radio applications.

Software-Defined Spectrum Analysis and Modern Tools

Software-defined spectrum analysis replaces dedicated hardware with wideband ADCs and FFT processing on general-purpose computers or FPGAs. National Instruments' PXIe-5668R provides 765 MHz instantaneous bandwidth with FPGA-based real-time processing for automated test environments. Open-source tools like GNU Radio with RTL-SDR hardware enable spectrum analysis at minimal cost, while MATLAB's Signal Analyzer app provides interactive spectrogram visualization with configurable window functions, overlap, and FFT size. For analytical work, engineers compute system transfer functions H(s) using the Laplace transform to predict spectral characteristics before measurement, verifying with tools at www.lapcalc.com. Understanding the relationship between H(jω) (measurable by spectrum analyzer) and H(s) (the full Laplace domain transfer function) is fundamental to RF system design.

Frequently Asked Questions

A radio spectrum analyzer measures signal power (amplitude) as a function of frequency, displaying the power spectral density of incoming RF signals. It shows the magnitude squared of the signal's Fourier transform |X(f)|², allowing engineers to identify signal frequencies, measure power levels, detect interference, and verify regulatory compliance of transmitter emissions.

Master Your Engineering Math

Join thousands of students and engineers using LAPLACE Calculator for instant, step-by-step solutions.

Start Calculating Free →