A spectrum analyzer having a memory function to adopt a digital-data-based frequency sweep scheme while achieving performance comparable to performance of a high-speed FFT spectrum analyzer, and a method of controlling the spectrum analyzer, in which the spectrum analyzer includes: an ADC for converting a BWP signal, which is at least one analog unit frequency band signal, into a digital data sample at a predetermined sample rate according to a span set by a user; a digital sweep part for sweeping the data sample passed through the ADC while digitally decimating the data sample through a decimation processing block having a two-stage cascaded structure, and processing the swept data sample to increase a frequency sweep speed; and a control unit for controlling the digital sweep part according to various items input, set, and selected by the user to perform spectrum analysis and output a spectrum analysis result.

A spectrum analyzer having a memory function to adopt a digital-data-based frequency sweep scheme while achieving performance comparable to performance of a high-speed FFT spectrum analyzer, and a method of controlling the spectrum analyzer, in which the spectrum analyzer includes: an ADC for converting a BWP signal, which is at least one analog unit frequency band signal, into a digital data sample at a predetermined sample rate according to a span set by a user; a digital sweep part for sweeping the data sample passed through the ADC while digitally decimating the data sample through a decimation processing block having a two-stage cascaded structure, and processing the swept data sample to increase a frequency sweep speed; and a control unit for controlling the digital sweep part according to various items input, set, and selected by the user to perform spectrum analysis and output a spectrum analysis result.

A measurement system and method tests for spurious emissions included in a signal transmitted from a mobile terminal in a shorter time than before. The system includes: a band division unit for dividing the measurement frequency band into a plurality of divided bands; a first spurious measurement control unit which causes a measurement device to measure the spurious emissions of the signal to be measured in each divided band and the peak power of the spear in each divided band; and a first pass/fail determination unit that determines whether or not pass determination criteria is satisfied. The first pass/fail determination unit determines whether the peak power does not exceed the threshold of the pass determination criteria in each divided band. The threshold value of the pass determination criteria is lower than the threshold of the standard determination criteria defined by the 3GPP standard.

A measurement system and method tests for spurious emissions included in a signal transmitted from a mobile terminal in a shorter time than before. The system includes: a band division unit for dividing the measurement frequency band into a plurality of divided bands; a first spurious measurement control unit which causes a measurement device to measure the spurious emissions of the signal to be measured in each divided band and the peak power of the spear in each divided band; and a first pass/fail determination unit that determines whether or not pass determination criteria is satisfied. The first pass/fail determination unit determines whether the peak power does not exceed the threshold of the pass determination criteria in each divided band. The threshold value of the pass determination criteria is lower than the threshold of the standard determination criteria defined by the 3GPP standard.

A method of processing power signals is provided. The method includes: receiving an analog poly-phase signal associated with power delivered using alternating current (AC); converting the analog poly-phase signal to a digital poly-phase signal sampled at a first sampling rate; detecting a fundamental frequency of the analog poly-phase signal; determining a second sampling rate, wherein the second sampling rate is based on and tracks the fundamental frequency; resampling the digital poly-phase signal at the second sampling rate; for each cycle of the resampled digital poly-phase signal: transforming the resampled digital poly-phase digital signal to a frequency-domain signal; calculating a phase angle of the reference voltage component; adjusting the resampled digital poly-phase signal by compensating the calculated phase angle; and transforming the adjusted resampled digital poly-phase signal to an updated frequency-domain signal using FFT; and calculating one or more measurements based on the updated frequency-domain signal.

The invention is directed to methods for radio frequency spectral analysis. Accordingly, flight instructions are executed on a first UAV to fly in a first flight pattern relative to a signal source. The first UAV detects radio signal(s) from the signal source and associated signal data. Flight instructions are concurrently executed on a second UAV to fly in a second flight pattern, relative to the first flight pattern of the first UAV. The second UAV also detects radio signal(s) from the signal source and associated signal data. The stored signal data from the drones may then be processed for visualization.

A method and apparatus for estimating the frequency of a dominant periodic component in an input signal by modelling the input signal using auto-regressive models of several different orders to generate candidate frequencies for the periodic component, generating synthetic sinusoidal signals of each of the candidate frequencies, and calculating the cross-correlation of the synthetic signals with the original signal. The frequency of whichever of the synthetic signals has the highest cross-correlation with the original signal is taken as the estimate of the frequency for the dominant periodic component of the input signal. The method may be applied to any noisy signal which has a suspected periodic component, for example physiological signals such as photoplethysmogram signals, and in the estimation of heart rate and breathing rate from such physiological signals.

A method and apparatus for estimating the frequency of a dominant periodic component in an input signal by modelling the input signal using auto-regressive models of several different orders to generate candidate frequencies for the periodic component, generating synthetic sinusoidal signals of each of the candidate frequencies, and calculating the cross-correlation of the synthetic signals with the original signal. The frequency of whichever of the synthetic signals has the highest cross-correlation with the original signal is taken as the estimate of the frequency for the dominant periodic component of the input signal. The method may be applied to any noisy signal which has a suspected periodic component, for example physiological signals such as photoplethysmogram signals, and in the estimation of heart rate and breathing rate from such physiological signals.

A digital receiver comprising at least two reception pathways, the method carries out a digital inter-correlation of the signals obtained as output from at least two filters of different central frequencies and different ranks, the rank and the central frequency of the filters being chosen as a function of a determined frequency-wise search domain. For a determined search domain, the various sampling frequencies of the reception pathways are chosen so that the ambiguous frequencies resulting from the spectral aliasings vary as a monotonic function of the true frequency of the signals.

A digital receiver comprising at least two reception pathways, the method carries out a digital inter-correlation of the signals obtained as output from at least two filters of different central frequencies and different ranks, the rank and the central frequency of the filters being chosen as a function of a determined frequency-wise search domain. For a determined search domain, the various sampling frequencies of the reception pathways are chosen so that the ambiguous frequencies resulting from the spectral aliasings vary as a monotonic function of the true frequency of the signals.