1761 results about "Signal wave" patented technology

The invention provides a wind generating set fault monitoring method and system based on voiceprint recognition, and the method comprises the steps: collecting gear box voiceprint signal data in real time, recording signal fluctuation caused by gear surface wear, and obtaining an original signal data set containing a frequency spectrum high-frequency component enhancement feature; a time-frequency analysis method is adopted for the original signal data set, non-linear interference of vibration signals is recognized, multi-scale decomposition is carried out, initial wear frequency spectrum narrow-band characteristics and medium-term harmonic components are separated out, and a frequency spectrum component set is obtained; extracting characteristic parameters related to modulation depth abnormal fluctuation from the frequency spectrum component set, identifying a gear pair meshing frequency change rule, and determining a distribution mode of a tooth surface contact noise proportion; and if the feature matching result shows that the deviation between the spectrum high-frequency component diffusion distortion feature and the reference feature library exceeds a threshold value, adding the tooth surface fatigue crack noise feature into the feature library to obtain a target feature library.

The invention relates to the technical field of electromagnetic flowmeter calibration, and discloses an electromagnetic flowmeter online calibration system and an acquisition and storage device. The system comprises a signal acquisition module, a data processing module, an error analysis module, a parameter calibration module and a real-time monitoring module. The signal acquisition module captures an original signal waveform through a multi-channel sensor array and acquires flow signal data to generate a state set; the data processing module uses a wavelet packet transformation and adaptive filtering combined algorithm to reduce noise and extract features; the error analysis module constructs a dynamic time warping error matching model to obtain an error correction coefficient; the parameter calibration module adopts a fuzzy control and proportional integral differential composite strategy, and adjusts excitation current and electrode sensitivity according to an error correction coefficient; the real-time monitoring module establishes a rolling optimization model with time-varying constraints, and generates a calibration instruction in combination with signal stability and power consumption limitation. According to the system, online accurate calibration of the electromagnetic flowmeter is realized, and the measurement accuracy and the equipment operation stability are improved.

The invention discloses an underground operation and maintenance method and system based on big data analysis, and relates to the technical field of coal mine underground operation and maintenance. The underground operation and maintenance method based on big data analysis comprises the following steps: evaluating the stability performance of a sensor; evaluating signal fluctuation; evaluating sensor interference; and operation and maintenance feedback. According to the method, the sensor stability performance evaluation value is obtained through underground sensor monitoring data, whether stability adjustment is carried out or not is judged, then the signal fluctuation evaluation value is obtained by combining the signal fluctuation data and the sensor stability performance evaluation value subjected to stability adjustment, and whether signal fluctuation adjustment is carried out or not is judged. A sensor interference evaluation value is obtained by combining the signal fluctuation evaluation value obtained after signal fluctuation adjustment and sensor interference data, whether sensor interference adjustment is carried out or not is judged, and finally operation and maintenance feedback is carried out, so that the effect of improving the underground operation and maintenance efficiency is achieved. The problem of low underground operation and maintenance efficiency based on underground data in the prior art is solved.

The invention discloses an up-conversion nanoprobe for detecting tyrosinase through dual-signal output and application of the up-conversion nanoprobe, and relates to the technical field of nano biological materials, the up-conversion nanoprobe comprises UCNPs, tyramine and iron ions; the UCNPs has a core-shell structure, beta-NaYF4: Yb, Er is taken as a core, and NaYF4 is taken as a shell; according to the up-conversion nanoprobe disclosed by the invention, by integrating the advantages of a fluorescence determination method and a colorimetric method, the dual-signal self-calibration capability is formed; according to the method, the UCL signal excited by near-infrared light is utilized, the detection precision is greatly improved, and an intuitive and convenient method is provided for detection of tyrosinase through colorimetric reaction; and a dual-signal output detection mode effectively relieves signal fluctuation, so that the accuracy and reliability of tyrosinase analysis are ensured.

A device implementing a nonlinear activation function including a material having nonlinear susceptibility phase-matching a coherent nonlinear interaction involving a signal comprising a signal wavelength and a bias comprising a bias wavelength, so that (1) a first phase difference between the signal and the bias induces the interaction comprising second harmonic generation (generating a second harmonic of the bias wavelength) or sum frequency generation (generating a sum frequency of the bias and the signal, and (2) a second phase difference between the signal and the bias induces the interaction comprising parametric amplification amplifying the bias and attenuating the signal. A positive input to the nonlinear activation function is represented by the signal having an input energy and the first phase difference. A negative input is represented by second phase difference. The output is an output energy of the signal as function of the input energy.

The invention discloses a detection and analysis system for an oil-controlling and soothing extract, particularly relates to the field of extract detection, is used for solving the problem of accurate quantitative analysis of complex components, and is characterized in that omnibearing characteristics of a sample are synchronously acquired and captured through multiple spectrums, and the information is fused into a high-dimensional data framework, so that the limitation of a single spectrum is avoided; thirdly, noise is removed through accurate calibration, sparse decomposition and cross-modal verification are combined, and it is ensured that extracted component signals truly reflect chemical characteristics and are not covered by redundant interference; on the basis, a clear signal of a target active component is further separated by utilizing dynamic convolution and an attention mechanism, and irrelevant background influence is eliminated; finally, through segmented modeling and geometric constraint, absorbance change is accurately converted into concentration data, and the concentration data can be kept stable even under the background fluctuation or nonlinear condition, so that the quantitative inversion error of the active component is reduced under the scene of background signal fluctuation or non-uniform optical path, and the accuracy of a determination result is improved.

The invention provides a baseband radio frequency signal data feedback processing method based on vector modulation, and the method comprises the steps: firstly receiving a baseband signal data set transmitted by a target radio frequency link in a preset frequency band, and the baseband signal data set comprises a plurality of signal frame original modulation parameters and corresponding radio frequency feedback signal waveforms; calculating a feedback error index composed of a phase offset, an amplitude distortion factor and a spectrum leakage factor according to a radio frequency feedback signal waveform, quantifying a modulation error, carrying out time-frequency domain conjoint analysis on the feedback signal waveform, extracting an error feature vector, inputting the error feature vector into a pre-training model for cross-frame correlation learning, and carrying out the correlation learning; according to the method, a dynamic adjustment parameter sequence containing a time sequence dependency relationship is generated, and finally a closed-loop feedback control link is constructed based on the dynamic adjustment parameter sequence and original modulation parameters, so that precise processing and optimal control of baseband radio frequency signals are realized, and the signal transmission performance is effectively improved.

The invention discloses a GPS interference phased array monitoring direction-finding antenna system for a 1575 frequency band, and relates to the technical field of intelligent antennae, comprising a data integration module for integrating data of satellite ephemeris, carrier attitude and airspace coverage through a weighted average method and generating an environment parameter set, a prediction calibration module for predicting the data of the satellite ephemeris, the carrier attitude and the airspace coverage through a weighted average method and generating an environment parameter set, and a direction-finding antenna module for performing direction-finding on the environment parameter set. The phase drift prediction module is used for inputting an environment parameter set into a bidirectional LSTM network, obtaining a phase drift prediction value, carrying out nonlinear calibration on the phase drift prediction value by adopting a Kalman-particle hybrid filtering algorithm, and synchronously monitoring an IQ signal by utilizing a closed-loop feedback mechanism, and the beam generation module is used for carrying out orthogonal modulation and radio frequency up-conversion processing on the IQ signal, and outputting the processed IQ signal. According to the method, the bidirectional LSTM network is combined with the Kalman-particle hybrid filtering algorithm, so that phase drift caused by factors such as carrier vibration and the like can be accurately predicted and calibrated in real time.

The invention relates to the field of magnetic field generation, and discloses a multi-mode array magnetic field generation system and method. The single excitation source matrix excitation comprises an FPGA main control chip and a DDS signal generation module, a DDS chip reads a signal waveform stored in an ROM, a keying module is combined with a PLL clock signal module and an amplification circuit, signals with adjustable amplitude, frequency, phase and duty ratio are achieved, excitation is applied to an array coil through bipolar D / A conversion to generate magnetic fields of different modes, and the magnetic fields of different modes are generated. The Hall magneto-dependent sensor is combined to adjust the angle and direction of the generated magnetic field in real time, and the focusing angle of the magnetic field is dynamically changed. The array coil is excited by generating a plurality of current signals with different amplitudes, frequencies, phases, duty ratios and directions, and the Hall magneto-dependent sensor above the coil is combined, so that the energy and direction of an array magnetic field are controllable, the magnetic field generation efficiency is improved, and the detection target is enhanced.

The invention discloses a control system for two-wheeled vehicle communication equipment, which relates to the technical field of communication equipment control and comprises a weak signal detection module, a signal fluctuation analysis module, a connection interruption evaluation module, a dynamic control optimization module and a self-adaptive adjustment module. The signal fluctuation analysis module is used for analyzing the network signal intensity fluctuation degree of the communication equipment in a weak signal environment based on the acquired network signal fluctuation information, and acquiring connection interruption risk information of the communication equipment in real time if the fluctuation degree exceeds a preset threshold value; and the connection interruption evaluation module is used for evaluating the connection interruption risk of the communication equipment under the condition of network signal fluctuation when the two-wheeled vehicle enters the weak signal environment. The problems of unstable connection, frequent disconnection and high power consumption of two-wheeled vehicle communication equipment in a weak signal environment are solved, intelligent detection, accurate evaluation, dynamic optimization and adaptive adjustment are realized, and the communication stability and the equipment cruising ability are improved.

Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive a reference signal from a network node. The reference signal may be associated with a beam, of a set of beams. Each beam of the set of beams may be associated with a respective beam index. The UE may determine a probability associated with an adjustment of the beam. The probability may indicate whether the beam will change over a duration from a first beam associated with a first beam index to a second beam associated with a second beam index based on the reference signal. The UE may transmit an indication of the probability associated with the adjustment of the beam to the network node.

The invention provides an isolation switch control device with a fault monitoring function, and relates to the technical field of electric power automation, and the device comprises an information collection module which collects the current information in real time during the operation of an opening and closing drive motor, and transmits the current information to a circuit protection module; the circuit protection module performs feature extraction on the current information in a mode of solving a signal waveform envelope line; whether the disconnecting switch has a fault is determined according to the current signal characteristics, and a control instruction is issued to the variable frequency driving module according to a fault result, or a key monitoring prompt is sent to the key monitoring module; the variable frequency driving module controls the operation state of the opening and closing driving motor according to the issued control instruction; and when the key monitoring module receives the key monitoring prompt sent by the circuit protection module, the monitoring frequency of the isolation switch is increased. According to the scheme, the abnormal state of the isolating switch can be monitored in the opening and closing process, so that serious accidents caused by faults of the isolating switch are reduced.

A physical quantity detecting device (10) detects a plurality of different physical quantities on the basis of an output signal waveform. A strain sensor (3) as one sensor element outputs a sensor signal waveform (15) having a reference level (151), a positive level positively changing from the reference level (151), and a negative level negatively changing from the reference level (151). An estimating unit (4) estimates a first physical quantity corresponding to a peak value (152) of the positive level and a second physical quantity corresponding to a peak value (153) of the negative level on the basis of the sensor signal waveform (15) output by the strain sensor (3).

An electronic device may be mounted to a main body of a removable case. The case includes a cover that rotates between open and closed positions. The device may convey wireless data and / or a control signal with the removable case over radio-frequency connectors, near-field communications (NFC) coils, connector electrodes, and / or wired data connectors. The removable case may relay the wireless data between the electronic device and a communications satellite in space. The case may include a phased antenna array in the cover. In the open position, the cover may point the phased antenna array towards the sky. The removable case may include beamforming circuitry in the cover and coupled to the phased antenna array. The control signal may control the beamforming circuitry to produce, using the phased antenna array, a signal beam oriented towards the communications satellite.

The invention relates to a double-end traveling wave fault location method based on weighted Minkowski distance and cubic spline interpolation. The method comprises the following steps: performing smooth fitting expansion processing on fault waveform data W through cubic spline interpolation; training a traveling wave head clipping model, and automatically positioning and clipping a wave head region Wcs; respectively recording the Wcs after the traveling wave processing at the two ends as Wa and Wb, translating one waveform, and calculating a weighted Minkowski distance dist; when dist is minimum, the translation amount is the time difference delta t when the traveling wave reaches the two ends for the first time. Through cubic spline interpolation, under the condition of low sampling rate, smooth fitting expansion is carried out on the signal waveform, the actual error range is obviously reduced, and the positioning precision is improved; according to the method, the weight of the distance near the fault moment is increased, the effect of highlighting the fault point is achieved, for the noisy waveform, noise reduction and other operations which can change the original waveform can be not carried out, the time difference delta t of the wave heads of the two fault traveling waves can be calculated, and the measurement error existing in the practice of the prior art is reduced.

The invention discloses an OFDM-LFM (Orthogonal Frequency Division Multiplexing-Local Frequency Modulation) integrated signal waveform receiving method and equipment based on fractional Fourier transform, LFM and OFDM are combined and improved, an OFDM-LFM integrated radar communication signal taking an orthogonal LFM signal as a subcarrier is adopted, and as the LFM subcarrier has larger Doppler tolerance, compared with a normal subcarrier, the OFDM-LFM integrated signal waveform receiving method and equipment based on fractional Fourier transform have higher Doppler tolerance, the radar communication signal can be received more accurately. The method not only can improve radar distance resolution and spectral efficiency, but also has a strong capability of avoiding Doppler effect, and can reliably transmit information, and when OFDM-LFM signals are received, in order to solve the problems of subcarrier frequency linear transformation, radar parameter extraction and the like, based on the sensitivity of fractional Fourier transform (FRFT) to LFM signals, the method can be used for solving the problems of subcarrier frequency linear transformation, radar parameter extraction and the like. According to the invention, the FRFT is used as the integrated signal receiver, the separation of the integrated signal communication receiver and the radar receiver is realized, and the system performance is improved while the complexity of the system is reduced.

A base station includes a controller that notifies a terminal device of first information regarding a signal waveform to be used in downlink communication in an initial connection procedure performed with the terminal device among a first signal waveform and a second signal waveform and perform the downlink communication with the signal waveform to be used based on the first information.

The embodiment of the invention provides a transformer defect detection system based on voiceprint detection and a method thereof. The method comprises the following steps: firstly, acquiring a sound wave signal of a detected transformer collected by a sound wave sensor, then, carrying out time-frequency analysis on the sound wave signal to obtain voiceprint characteristic parameters, then, carrying out local waveform characteristic extraction on the sound wave signal to obtain a sequence of sound wave fragment signal waveform characteristic vectors, and finally, carrying out local waveform characteristic extraction on the sequence of the sound wave fragment signal waveform characteristic vectors. The voiceprint characteristic parameters are integrated into a sequence of the sound wave fragment signal waveform characteristic vectors to obtain a voiceprint characteristic embedded guiding sound wave signal global waveform characteristic vector, and finally, whether the detected transformer has a fault or not is determined based on the voiceprint characteristic embedded guiding sound wave signal global waveform characteristic vector. Therefore, transformer fault detection and identification can be realized.

The invention discloses a communication link switching method and a related device, channel quality is calculated by adopting multiple channel quality indexes of links, the problem of wrong switching caused by fluctuation of a single index can be effectively avoided, a link switching threshold value and a switching judgment period are updated according to the multiple channel quality indexes of each link in a preset time window, and the switching efficiency is improved. According to the method, the link switching threshold and the switching judgment period can adapt to signal fluctuation in a low-altitude complex environment, the error switching rate and the communication interruption risk are reduced, unnecessary frequent switching can be avoided, and resource consumption is reduced.

The invention discloses an ad hoc network communication system without a signal area, particularly relates to the technical field of wireless communication, and is used for solving the problem that a connectivity critical state caused by node density or mobility change in a low-density network is not fully considered in an existing dynamic routing protocol. The network connectivity critical state is pre-judged by acquiring node position coordinates and communication radiuses in real time and combining the average node spacing and the dispersion in the moving direction; screening a high-priority detection node based on an obstacle avoidance cooperative angle variance and a virtual pheromone concentration in a critical state, and adaptively adjusting a detection message sending frequency according to a node moving speed; constructing a path stability evaluation model by fusing the link survival duration, the node residual energy and the signal intensity fluctuation rate, dynamically screening a high-stability path as a main transmission link, and taking the rest lists as standby links; and monitoring the signal fluctuation characteristics of the main link in real time, and quickly switching to the path with the optimal comprehensive stability in the standby link in an abnormal state.

The invention relates to the technical field of cable fault testing, in particular to a multi-core cable fault testing system and method, and the method comprises the steps: determining a fault generation coefficient of a target core wire testing current signal based on the difference between periods where all adjacent signal wave crests in the target core wire testing current signal are located and a periodic parameter; determining the composition richness of the target core wire test current signal based on the similarity of related data sets between the target core wire and all other core wires under different voltage conditions and the signal amplitude distribution near any maximum value point in the target core wire test current signal; and performing forward fusion on the composition richness and the fault occurrence coefficient, adjusting a preset initial decomposition interval scale, screening part of component signals for reconstruction, and performing fault detection on the reconstructed signals. According to the invention, accurate analysis of the test current signal is realized, and the accuracy of fault diagnosis is improved.

The invention relates to the technical field of fault diagnosis, in particular to an SMT production line equipment fault diagnosis method and system based on the Internet of Things, and the method comprises the following steps: obtaining multiple types of signals, aligning a time window, judging that the trend is consistent and fluctuation is synchronous to generate a sudden change event, recognizing an intersection point, extracting a key response position, and outputting an inflection point node number. And constructing a response time sequence and a propagation path, identifying abnormal nodes, and generating a fault traceability result. According to the invention, through time alignment and trend linkage identification of current, temperature and acceleration signals, fusion of trend direction judgment and fluctuation synchronization relation, a cross-equipment linkage sudden change identification mode is established, key response points are extracted through cross positioning of a jump terminal point and a vibration peak value, and a dynamic judgment mechanism of inflection point nodes is formed. In combination with a response sequential sequence and a chain path structure, local signal fluctuation analysis is converted into perception, and the judgment accuracy and traceability of abrupt change abnormity are effectively improved.

The invention provides an anomaly detection method of an ultrasonic gas meter and the ultrasonic gas meter, and relates to the technical field of flow monitoring. The invention provides a more accurate and timely anomaly detection method aiming at the problem that an existing detection method for judging whether an instrument is abnormal or not only by judging flight time of an ultrasonic gas meter is not timely and accurate enough in anomaly response. The method comprises the following steps: exciting a first transducer according to a preset frequency to enable the first transducer to emit an ultrasonic signal; the second transducer receives the ultrasonic signal transmitted by the first transducer and generates an echo signal waveform; and waveform features are extracted from the echo signal waveforms, and if the waveform features do not conform to a preset rule, it is judged that detection of the ultrasonic gas meter is abnormal. In addition, according to different identification results, different processing modes are adopted, the anti-interference capability of the instrument is improved, and the abnormal detection of the instrument is more accurate.

The invention discloses an optical fiber winding detection method and device, and the method comprises the steps: obtaining an optical pulse transmission signal transmitted by an optical time domain reflectometer to a to-be-detected optical fiber, and receiving a reflected optical pulse reflection signal; respectively carrying out signal waveform feature extraction on the optical pulse transmission signal and the optical pulse reflection signal to obtain a transmission signal waveform semantic feature map and a reflection signal waveform semantic feature map; processing the transmitted signal waveform semantic feature map and the reflected signal waveform semantic feature map to obtain a transmitted signal waveform semantic saliency feature map and a reflected signal waveform semantic saliency feature map; performing nonlinear correlation interaction processing on the transmitted signal waveform semantic saliency feature map and the reflected signal waveform semantic saliency feature map to obtain a transmitted signal-reflected signal waveform semantic correlation feature map; the classifier outputs an optical fiber winding identification result according to the transmitted signal-reflected signal waveform semantic association feature map; the method can improve the accuracy of optical fiber winding identification.

The invention relates to a power distribution network carrier communication system access security detection method. The method comprises the following steps: acquiring environmental parameter data including a power supply voltage value, a temperature value and a humidity value through real-time monitoring, and introducing a data processing and signal analysis algorithm based on artificial intelligence and deep learning at a rear end to analyze an original signal and the environmental parameter data; waveform semantic features in an original signal and multi-modal time sequence correlation features of environmental parameter data are learned and captured, and then cross-modal joint semantics between the waveform semantic features and the multi-modal time sequence correlation features are utilized to correct waveform semantics of the original signal based on environmental fluctuation, so that a more robust equipment fingerprint is obtained. Therefore, the influence of environmental interference on equipment fingerprint identification and extraction can be reduced in a more intelligent manner, so that the stability and the accuracy of fingerprint extraction and matching are enhanced, the access safety of a power distribution network carrier communication system is ensured, and the stability and the reliability of a power system are guaranteed.

Disclosed are systems, apparatuses, processes, and computer-readable media for wireless communications. For example, an example of a process includes transmitting, to a reconfigurable intelligent surface (RIS), a plurality of reference signal beams in a plurality of directions. The process may further include receiving, from the RIS, a plurality of reflection reference signal beams in the plurality of directions based on a plurality of backtracking reflection coefficients. The process may include measuring a signal strength of each reflection reference signal beam in each direction of the plurality of directions for each backtracking reflection coefficient of the plurality of backtracking reflection coefficients. The process may further include determining, basing on measuring the signal strength, a selected beam direction from the plurality of directions and a selected backtracking reflection coefficient of the plurality of backtracking reflection coefficients.

The invention discloses a host USB structure verification management system based on model fusion, and particularly relates to the field of computer security. The system comprises a data acquisition layer for acquiring a protocol data packet, an electrical signal waveform and equipment logic state information of a USB interface in real time, and generating a standardized multi-modal data stream through time alignment processing; the feature extraction layer is used for extracting modeling features from the standardized multi-modal data stream and encoding the modeling features into a structured matrix; the model fusion layer is used for fusing and outputting joint verification confidence through a protocol rule model, an anomaly detection model and a simulation model; the decision management layer executes a three-level verification strategy in sequence; the user interaction layer provides a visual monitoring and manual feedback interface and supports dynamic model replacement. According to the method, the structural legality of the USB equipment is verified through multi-model cooperation, real-time monitoring and risk level-to-level management of the USB equipment are achieved, the safety and compliance of the host terminal are improved, and the method is suitable for enterprise-level USB equipment protection scenes.

The invention relates to the technical field of physical health data analysis, in particular to a teenager physical training method and system based on data analysis, and the method comprises the following steps: dividing a load signal into a low-frequency band, a bandwidth frequency band and a high-frequency band based on the load intensity data in teenager training, analyzing the long-term change trend and fluctuation range of the load of the low-frequency band, and calculating the long-term change trend of the load of the high-frequency band; stability parameters are calculated in combination with bandwidth frequency band signal fluctuation, the high-frequency-band short-time load change rate and change rate distribution are analyzed, and a frequency band distribution parameter set is obtained. According to the invention, through load signal multi-band decomposition and parameterization processing, independent calculation and comprehensive analysis of load characteristics are realized, the dynamic change capture capability is enhanced, and through association of cumulative load and time distribution characteristics, dynamic interaction data support is provided, and load risk points and distribution areas are accurately identified. The intensity, time and frequency adjustment strategies are optimized, load balance and action coordination are achieved, overload and deviation risks are reduced, and the scientificity and controllability of teenager training are improved.

The invention discloses a signal detrending method based on sliding window statistics and dynamic wave crest correction. The method comprises the step of realizing accurate extraction of signal trend and fluctuation characteristics through a double-window dynamic adjustment mechanism of a mean value window and a standard deviation window. A detection threshold value is dynamically adjusted by analyzing the change trend of the historical wave crest amplitude, and the real-time tracking capability of signal fluctuation is ensured; meanwhile, different parameter configurations are preset for different application scenes, the problem of missing detection or misjudgment generated when the amplitude of a fixed threshold algorithm changes suddenly is solved, and the wave crest recognition accuracy is improved. Based on a dynamic threshold algorithm, wave peak start and end points are automatically identified, a linear interpolation technology is adopted to calculate slope of each interval, fitting parameters are dynamically adjusted through residual analysis, and finally low-frequency trend terms and high-frequency characteristic components are effectively separated through difference operation of original signals and fitting signals. The problem of fitting deviation caused by non-uniform sampling can be effectively solved.

Measuring MDEVM of a DUT includes splitting an RF signal output by a DUT into first and second RF signals; acquiring and digitizing the first and second RF signals in first and second channels without demodulating the first and second RF signals; performing equalization of the first and second RF signals; measuring first and second modulation distortion (MD) error vectors of the equalized first and second RF signals; performing cross-correlation of the first and second MD error vectors across the first and second channels; averaging the cross-correlated MD error vectors over symbols and packets of the RF signal; and dividing the averaged cross-correlated MD error vectors by signal power of an ideal signal to obtain cross-correlated MDEVMs over a time period or bandwidth of a waveform of the RF signal, where performing the cross-correlation suppresses contribution of uncorrelated noise.