219 results about "Noise threshold" patented technology

The invention relates to the field of concrete crack monitoring, in particular to a solid waste aggregate concrete crack real-time monitoring method and system, and the method comprises the steps: collecting sensor data in real time; calculating a deviation value between the current data and the initial reference data; when the deviation value exceeds a threshold value, the deviation value is used for compensating the subsequently collected sensor data; updating the initial reference data by using the mean value of the compensated data in the previous period; processing the compensated data in different channels, extracting strain accumulation trend characteristics in a long-term channel through a large time window, and extracting acoustic emission instantaneous characteristics in a short-term channel through a small time window; setting a long-term feature weight to be higher than a short-term feature weight, calculating a long-term feature change rate, and when the change rate is stable, improving the long-term weight and reducing the short-term weight, and filtering features lower than a noise threshold in a short-term channel; and fusing the weighted long-term features with the effective short-term features, and inputting the fused features into a pre-training model to obtain a fracture state prediction result in a future predetermined period.

The invention discloses a self-adaptive filtering method and system for an intelligent electric energy meter, and relates to the technical field of power grid signal processing, and the method comprises the steps: obtaining a power grid voltage and current signal set collected by a target intelligent electric energy meter historically, and obtaining a signal noise spectrum data set and a noise level evaluation result through spectrum analysis and noise level evaluation; if the result exceeds a preset noise threshold value, identifying an interference type and building a noise adaptive filtering multi-channel, integrating and deploying the noise adaptive filtering multi-channel into a target intelligent electric meter to complete signal filtering test and effect evaluation, and dynamically optimizing and generating an electric energy meter adaptive filtering multi-channel based on the obtained multi-channel filtering effect index parameter; and finally, signal filtering closed-loop control is realized. The technical problem that a traditional electric energy meter is weak in filtering pertinence and cannot adapt to dynamic noise of a power grid in electric power related scenes with complex dynamic interference is solved, and the technical effects that the electric variable measurement accuracy of the electric energy meter is improved, and the adaptive capacity of the electric energy meter to different interference scenes is enhanced are achieved.

The invention discloses a high-frequency oscillation mode identification method and device of a power system, equipment and a medium. The method comprises the following steps: acquiring an original signal from the power system; performing parameter optimization on a preset variational mode decomposition model by adopting a black wing plinux optimization algorithm to obtain a target variational mode decomposition model; calling a target variational mode decomposition model to decompose the original signal to obtain a plurality of intrinsic mode components; calculating an autocorrelation coefficient corresponding to each intrinsic mode component, and selecting at least one oscillation characteristic component according to a comparison result of the autocorrelation coefficient and a preset noise threshold; and carrying out oscillation mode identification on each oscillation characteristic component by adopting a preset energy operator, and determining corresponding dominant high-frequency oscillation information. Therefore, high-frequency oscillation information identification of the broadband signal of the power grid is realized, and important oscillation information in the broadband signal is effectively prevented from being lost.

The invention discloses a cable defect analysis method and system in a cable laying process, and the method comprises the steps: dividing a current data sequence according to a preset data division strategy, obtaining at least one current data sub-sequence, and obtaining cable images of different monitoring positions according to the at least one current data sub-sequence; preprocessing the cable image to obtain a target cable image, and performing cable contour and background region segmentation on the target cable image to obtain a cable contour image; calculating a cable area based on the cable contour image, and extracting cable surface features; analyzing the surface features of the cable based on a set noise threshold, and removing noise features to obtain optimized surface features of the cable; and analyzing the surface features of the optimized cable based on the defect detection model, and outputting surface defect information. The accuracy and the real-time performance of defect detection are remarkably improved, the manual inspection cost and the leakage detection risk are reduced, and reliable guarantee is provided for safe operation of the cable.

The invention provides a force direction feedback system and method of pneumatic pressure. The system generates a first oscillation signal changing along with air pressure and a second oscillation signal with fixed frequency through a signal conversion module; and the counter counts the cycles of the two paths of oscillation signals. The back noise calibration module samples environment back noise by using a second oscillation signal in a frequency division manner, and eliminates back noise interference in a force count value through a subtractor, so that the problem of detection deviation caused by environment air pressure fluctuation is solved; and the dual-threshold comparison module screens the difference signal through a back noise threshold and an anti-shake threshold, generates a force conversion value, and avoids error output caused by slight fluctuation and shake. The differential operation module processes the force conversion value in combination with the second oscillation signal, the accurate pneumatic force value is output through signal correlation, the pneumatic direction can be distinguished by means of comparison with the fixed reference, and finally accurate and stable feedback of the pneumatic pressure force and direction is achieved.

The invention relates to the field of image processing, in particular to a fish and shrimp denoising enhancement and intelligent identification method based on a two-dimensional sonar image, which comprises the following steps: extracting a sonar image water background, dividing regions and calculating a signal-to-noise ratio, dynamically adjusting a noise threshold, and denoising to obtain a salient image. And a multi-rotation-angle convolution kernel set is constructed based on a size statistics preset ellipse parameter. And clustering salient image pixel points, setting a bounding rectangle as a suspected target area, and judging the consistency of continuous frame targets through an optical flow algorithm. And dynamically adjusting a convolution kernel weight enhancement image, training a YOLO model to recognize a target, superposing recognition results and providing statistical information. According to the method, the fish and shrimp targets with variable sizes and directions in the sonar image are accurately identified and tracked by utilizing dynamic noise threshold adjustment and a multi-angle convolution kernel set in combination with a denoising enhancement technology based on a signal-to-noise ratio and an optical flow algorithm, the limitation of a traditional method is effectively overcome, and reliable technical support is provided for target detection in a complex underwater environment.

The invention discloses a seabed obstacle identification method based on multi-beam point cloud data and related equipment. The method comprises the following steps: acquiring the multi-beam point cloud data of a target area; performing statistics on the basis of the elevation difference between the adjacent sounding point clouds to obtain a frequency-based elevation difference histogram; fitting an attenuation model according to the elevation difference histogram, determining a noise threshold value based on the attenuation model, and dividing the multi-beam point cloud data into a real terrain point cloud and a noise point cloud by using the noise threshold value; a multi-beam real terrain point cloud is obtained through iterative denoising division; and based on the multi-beam real terrain point cloud, obstacle identification is carried out by using the elevation slope, and obstacle information of the target area is obtained. According to the method, through the automatic processes of determining the noise threshold value through the fitting attenuation model and iterative denoising, a traditional interactive filtering method depending on experience of technicians is replaced, the data processing efficiency is greatly improved, and the method can be widely applied to the technical field of data processing.

The invention discloses a scene-adaptive multipath time delay alignment method and device for a wireless communication system, and the method comprises the steps: employing an SISO channel detection system to actually measure channel data, employing rectangular or RRC shaping filtering to generate a CAZAC oversampling sequence as a template function, calculating a cross-correlation matrix of an IQ signal and the template function, and enabling the CAZAC oversampling sequence to serve as the template function; a noise threshold is calculated based on the median power and the false alarm rate, dynamic threshold filtering is executed, a cross-correlation matrix after denoising is generated, and preliminary estimation of the time domain impulse response is completed; extracting multipath time delay and complex gain from the cross-correlation matrix by using an SAGE algorithm; drawing a power delay spectrum PDP for the channel impulse response; and performing alignment operation on the PDP in combination with the geographical location information of the transceiver during actual measurement. According to the method, the defect of traditional alignment in a severe scene is overcome, the statistical modeling accuracy is improved, the multipath time delay can be effectively aligned through experimental verification, and reliable support is provided for channel modeling.

A voice mixing conversion method includes: performing a noise reduction processing on the initial generated speech based on a noise threshold to generate a post-noise reduction speech; calculating a first quality score and a second quality score, wherein in response to a number of the initial generated speech being 1, the first quality score is calculated based on the initial generated speech, and the second quality score is calculated based on the post-noise reduction speech; and determining whether the first quality score is greater than the second quality score, wherein in response to the first quality score being greater than the second quality score, the initial generated speech is output, otherwise the post-noise reduction speech is output.

The invention provides a server fan speed regulation method and device based on a BMC (Baseboard Management Controller). The method provided by the invention comprises the following steps: determining the type of a server based on the condition that the server is equipped with a noise sensor; matching a corresponding noise determination method based on the server type, and determining a real-time noise value based on the noise determination method; comparing the real-time noise value with a noise threshold value, and determining a corresponding noise interval; acquiring a CPU utilization rate and a GPU utilization rate of the server; calculating a feedback value based on the CPU usage rate and the GPU usage rate; and in the noise interval, determining a corresponding speed regulation method based on a matching relationship between the feedback value and a plurality of feedback intervals, and regulating the speed of a fan on the server based on the speed regulation method. According to the server fan speed regulation method and device based on the BMC provided by the invention, dual optimization of heat dissipation efficiency and low noise is realized by intelligently regulating and controlling the rotating speed of the server fan.

The invention provides a control method and device of a twin-tub washing machine, the twin-tub washing machine and a storage medium. The method comprises the steps of obtaining operation noise of the twin-tub washing machine, and determining whether the operation noise is larger than a noise threshold value or not; under the condition that the operation noise is larger than the noise threshold value, operation parameters of a first barrel and a second barrel of the double-barrel washing machine are obtained; control parameters of the twin-tub washing machine are determined according to the operation parameters of the first tub, the operation parameters of the second tub and the operation noise, the control parameters are adopted to control the twin-tub washing machine so as to eliminate resonance of the twin-tub washing machine, and the control parameters comprise the control duration and the control rotating speed. The problems that an existing twin-tub washing machine is prone to causing the resonance phenomenon, the service life of equipment is shortened, and user experience is affected are solved.

A weather prediction method includes generating radiance differences as a difference between measured radiances from satellites and forecast satellite radiances generated by a radiative transfer model and forecasted state profiles output by a numerical weather prediction (NWP) model. When the radiance differences exceed a noise threshold, the method includes generating updated state profiles by generating radiance-sensitivities using a Jacobian model and the forecasted state profiles; constructing a Kalman-gain matrix from background error covariance (BEC) matrices and the radiance-sensitivities; generating filtered state-profile changes from the Kalman-gain matrix and the radiance differences; updating the state profiles by adding the filtered state-profile changes to the forecasted state profiles to yield updated state profiles.

The present invention relates to the technical field of correlation operations and discloses a correlation operation method. First, a sequence to be quantized is determined in two related sequences according to a quantization indication, and the sequence to be quantized is quantized based on a quantization bit width to obtain a quantized output sequence. Then, based on the calculated quantization noise sequence of the sequence to be quantized, the quantization error of the two related sequences is calculated, and the quantization error is compared with a preset noise threshold. When the quantization error is greater than or equal to the noise threshold, the quantization bit width is gradually increased to repeatedly quantize the sequence to be quantized until the quantization error is less than the noise threshold. When the quantization error is less than the noise threshold, a correlation operation is performed on the two related sequences to obtain a correlation operation result. The above method can adaptively adjust the quantization bit width based on the comparison result of the quantization error and the preset noise threshold, and achieve an optimized balance between computing performance and power consumption while ensuring the accuracy of the correlation operation.

The invention discloses a gas insulation cabinet partial discharge monitoring method and device based on edge calculation, and relates to the technical field of gas insulation cabinets. The method comprises the following steps: collecting environmental data and background electromagnetic noise signals of the gas insulation cabinet, calculating an environmental noise correlation coefficient by using a maximum information coefficient method, combining an environmental deviation value to obtain a comprehensive environmental disturbance index, and correcting a preset background noise threshold value to obtain a corrected noise threshold value; if the real-time electric signal amplitude exceeds the corrected noise threshold, marking the data as partial discharge signal data; denoising the partial discharge signal data by adopting an improved ensemble empirical mode decomposition adaptive noise method, and extracting a discharge feature vector; calculating the mahalanobis distance of each feature vector in the discharge feature vector sequence, obtaining the discharge similarity, obtaining a homologous discharge link, extracting the feature data of the homologous link, inputting the feature data into a BP neural network model based on a dung beetle optimization algorithm, outputting the type of partial discharge, and carrying out the early warning, thereby achieving the monitoring of the partial discharge of the gas insulation cabinet.

The invention discloses a household appliance control method, a household appliance and a storage medium, and relates to the technical field of household appliances, the household appliance control method comprises the following steps: determining user parameters of a user in a working area according to image data and / or audio data corresponding to the current working area of a target household appliance, obtaining a transfer coefficient between the target household appliance and the user; determining a noise threshold value corresponding to the user according to the user parameter; determining a noise value corresponding to the position of the user according to the current working condition of the target household appliance and the transfer coefficient; and if the noise value is greater than the noise threshold value, adjusting operation parameters of the target household electrical appliance so as to reduce noise generated by the target household electrical appliance and improve the use comfort of the household electrical appliance.

An active noise cancellation (ANC) system is provided with at least one loudspeaker to project anti-noise sound within a passenger cabin of a vehicle in response to receiving an anti-noise signal and at least one microphone to provide an error signal indicative of noise and the anti-noise sound within the passenger cabin. An adaptive filter controller is programmed to filter the error signal to obtain a noise reduction ratio, and to adjust a step size and / or leakage parameter based on a comparison of the noise reduction ratio to a noise threshold. A controllable filter generates the anti-noise signal based on the adjusted step size and / or leakage parameter.

The present invention relates to a silent control method, control device, and air conditioner for an air conditioner. The silent control method comprises: obtaining an indoor ambient temperature and an indoor set temperature; determining an indoor heat exchange requirement and a corresponding noise threshold value based on the indoor ambient temperature and the indoor set temperature; obtaining a noise detection value, and controlling the operating state of an indoor unit based on the indoor heat exchange requirement, the noise threshold value, and the noise detection value. This method differs from conventional silent control methods for air conditioners in that it uses ambient temperature and noise parameters as a basis for determination, adjusts the speed of the indoor fan, the speed of the sweep motor, and the operating angle of the air guide plate, and through linked control ensures the air conditioner's heat exchange capacity while achieving silent sweeping.

The invention discloses a waveform feature extraction method and system for irregular waveforms of a hyperspectral laser radar, and aims at solving the problem that asymmetric waveforms, weak echoes and overlapped echoes in multi-channel full-waveform laser radar signals are difficult to accurately decompose, modeling full-waveform signals collected by multiple spectral channels into superposition of echo components and background noise. A multi-channel waveform is preprocessed through noise threshold and pulse width combined constraint, the waveform position is determined by adopting a gravity center discrimination method, and time synchronization calibration of each channel signal is realized in combination with a multi-echo quality index. The method further utilizes a cubic B-spline function to carry out modeling on transmitted waveforms of all spectrum channels, carries out weighted accumulation on multi-channel echo signals to enhance weak echo signals, and adopts a multi-channel interconnection decomposition optimization strategy to realize accurate extraction of irregular waveform features under the constraint condition of keeping time parameters of sub-echoes of all the channels consistent.

The embodiment of the invention provides a method and device for reducing noise, electronic equipment and a storage medium, the method and device are applied to an intelligent bedstead, the intelligent bedstead comprises a plurality of boxes, a keel frame and a driving motor, the driving motor is used for driving any one of the boxes to move, the boxes are used for supporting the keel frame, and the keel frame is used for supporting the boxes. The method comprises the steps of determining a moving target box body and a target position of the target box body in response to a selection instruction of a user, and predicting moving noise generated when the target box body is driven by a driving motor to move from a current position to the target position at a preset speed; obtaining the sensitivity of a target user in a sleep state on the intelligent bed frame to noise; judging whether the moving noise is smaller than or equal to a noise threshold; and under the condition that the moving noise is greater than a noise threshold value, according to the sensitivity of the target user to the noise, determining a driving parameter of a driving motor so as to control the noise generated by moving the target box body within a preset time length to be less than or equal to the noise threshold value.

The utility model discloses a refrigerator press room noise monitoring device which comprises a plurality of sound acquisition devices, a sound analysis module and a control module. The vibration sensors are a microphone installed in a press chamber, a first vibration sensor installed on the outer surface of a compressor, a second vibration sensor installed on a refrigerant transmission pipeline, a third vibration sensor installed on a fan shell and a fourth vibration sensor installed on the outer surface of a condenser. Each sound collection device is electrically connected with the sound analysis module, the sound analysis module is used for processing noise collected by each sound collection device, the sound analysis module is electrically connected with the control module, and a noise threshold value corresponding to each sound collection device is preset in the control module; and the control module is used for comparing the processed noises with the corresponding noise thresholds respectively, and if the noises exceed the noise thresholds, an alarm is given, so that a user can process the noises in time.

The embodiment of the invention provides a water pump noise control method, a heat management system, electronic equipment and a vehicle. The water pump noise control method comprises the steps of obtaining a target rotating speed of a motor in response to that a detected noise value of a water pump exceeds a preset noise threshold value; acquiring motor parameters of the motor; calculating feedback torque distribution of the motor through the rotating speed prediction model, determining a target control strategy from a plurality of pre-configured control strategies based on the feedback torque distribution, and outputting a predicted rotating speed and parameter information of the motor; and outputting a corresponding voltage control signal to a driving circuit connected with the motor based on the predicted rotating speed. The change trend of the actual rotating speed is estimated by taking the target rotating speed as the expected value through the rotating speed prediction model to obtain the predicted rotating speed, the controller works according to the control strategy corresponding to the controller parameters, and on the basis, the predicted rotating speed outputs the corresponding voltage control signal to the driving circuit, so that the motor rotating speed of the motor can accurately reach the predicted rotating speed, and the driving efficiency is improved. And a better noise suppression effect is achieved.

This invention discloses a vibration signal denoising and feature extraction method based on wavelet adaptive thresholding, belonging to the field of vibration sensor signal processing technology. The method includes the following steps: Step 1, performing multi-level decomposition of the signal using a filter bank constructed based on discrete wavelet transform; Step 2, adaptively calculating the noise threshold; Step 3, implementing wavelet coefficient shrinkage denoising based on the SureShrink algorithm; Step 4, reconstructing the vibration signal based on quasi-discrete wavelet transform; Step 5, automatically extracting signal features based on a multi-layer recurrent neural network. This invention, through signal decomposition based on discrete wavelet transform and an adaptive thresholding denoising algorithm, reduces the error impact caused by the vibration sensor's own noise and environmental disturbances, retains most of the features of the original vibration signal, and establishes a multi-layer recurrent neural network for the denoised vibration signal to achieve automatic extraction of time features, providing an important foundation for the subsequent development of fault diagnosis and health monitoring algorithms.

The invention provides a channel estimation method based on a double-domain weighting-noise threshold, which comprises the following steps of: 1, time-frequency domain transformation: after receiving signals of a receiving end are subjected to time-frequency synchronization processing, extracting a pilot frequency sequence pilot, carrying out N-point FFT (Fast Fourier Transform) on the receiving signals, and converting the receiving signals to a frequency domain to obtain PILOT; performing N-point FFT (Fast Fourier Transform) on the time domain local pilot frequency sequence pilot to generate a frequency domain local pilot frequency PILOT; 2, calculating a frequency domain weighting coefficient: calculating the frequency domain weighting coefficient Coef according to the local pilot frequency PILOT and the current linear signal-to-noise ratio sn; step 3, channel estimation calculation: carrying out signal-to-noise ratio self-adaptive adjustment on the received signal of each frequency point through the operation; 4, inverse discrete Fourier transform: performing inverse Fourier transform on the channel estimation H after frequency domain weighting, and converting a frequency domain signal into a time domain signal to obtain h; step 5, extracting useful information: calculating and determining an optimal symbol length parameter L according to the maximum time delay extension of the system, performing optimization truncation on time domain data, retaining original values of the first L sampling points, endowing a zero value to subsequent sampling data exceeding the L point, and finally obtaining an optimized time domain result hL; 6, threshold judgment: within the range of the effective symbol length L, calculating a self-adaptive noise judgment threshold, implementing intelligent noise filtering processing on the truncated L-point data by using the threshold, eliminating a noise component through the threshold, and finally outputting a purified result hLR; and 7, zero padding: setting the length of the data block needing to be balanced as M, and setting the point number of channel estimation as N. When Mgt; when M is larger than N, time domain zero padding needs to be carried out on the hLR, the number of zero padding is M-N, and hLRZ is obtained; and 8, DFT: carrying out Fourier transform on the hLRZ to obtain a final complete channel estimation HLRZ.

This application discloses an intelligent detection method and system for corrosion defects in flood discharge tunnels, relating to the field of tunnel corrosion detection technology. The method includes: generating a cavitation number distribution cloud map of the entire flood discharge tunnel area based on historical operating data; marking areas with cavitation values ​​below a preset cavitation number threshold as theoretical high-risk areas; marking areas with cavitation noise intensity exceeding a preset noise threshold as measured noise active areas; spatially superimposing and comparing the theoretical high-risk areas and the measured noise active areas to determine cavitation confirmation areas, potential cavitation risk areas, and cavitation anomaly areas; outputting a surface damage index through a pre-trained cavitation damage assessment model; calculating a dynamic cavitation risk factor; and generating a structured corrosion defect detection report. This method solves the problems of low detection efficiency, limited detection range, and difficulty in accurately assessing corrosion risk in existing flood discharge tunnel corrosion detection methods.

The embodiment of the invention relates to the technical field of pulse diagnosis, and discloses a pulse analysis method based on a pulse diagnosis instrument, which comprises the following steps: processing a pressure change signal within a set time to obtain an original pulse waveform signal associated with a user; performing high-frequency denoising processing on the first pulse frequency signal according to a set noise threshold value; acquiring all wavelet coefficients associated with the high-frequency detail signal, traversing all the wavelet coefficients, determining that the absolute value of the wavelet coefficient at a certain point is greater than the absolute value of the wavelet coefficient adjacent to the wavelet coefficient, and taking the wavelet coefficient as a signal abrupt change point; generating a corresponding pulse image of the user based on the pulse condition data of the user within a set time range; and inputting the obtained pulse condition graph of the user into a pre-constructed standard pulse condition model to determine a pulse condition type result of the user, and outputting the pulse condition type result of the user. According to the scheme provided by the embodiment of the invention, the user can conveniently, quickly and accurately know the pulse condition and the physique state of the user, and the use convenience is improved.

The application belongs to the technical field of signal processing, and particularly relates to a non-coherent scattering ionospheric parameter non-ambiguous estimation method based on Monte Carlo, aiming to solve the problems of inaccurate parameter estimation and poor robustness in ionospheric parameter inversion in the prior art. The method comprises the following steps: receiving measured echo data, estimating the signal noise level and determining the prior information combination mode; obtaining an expected index based on a signal noise threshold mapping library, and judging whether a preset decision threshold is met; if the preset decision threshold is met, starting an optimization selection strategy based on Monte Carlo, and obtaining a candidate solution set; performing cluster analysis on the candidate solution set, selecting a solution with the optimal fitting degree from the solution cluster containing the largest number of solutions, and taking the solution as the final non-ambiguous estimation value. Through systematic Monte Carlo simulation, the application can quantitatively evaluate the inversion reliability under the current data condition, effectively avoid invalid calculation under adverse conditions such as excessive noise or insufficient prior information, and improve the robustness and success rate of estimation.

The invention provides a vehicle control method, a vehicle and a storage medium. The vehicle control method comprises the following steps: acquiring current geographic position information of the vehicle and environmental noise data around the vehicle; judging whether the geographical location information belongs to a preset mute area or not, and judging whether the environmental noise data is lower than a preset noise threshold value or not; and under the condition that the geographical location information belongs to the mute area and the environmental noise data is lower than a preset noise threshold value, when the vehicle executes locking operation, circuit conduction of the whistling device is blocked. According to the method, based on double judgment of the geographic position and the environmental noise, the scene needing to be prevented from generating noise can be accurately recognized, the vehicle locking prompt tone is automatically turned off, the high self-adaptive capacity is achieved, unnecessary noise pollution is effectively avoided, meanwhile, inconvenience caused by excessive intervention to a user can be prevented, and the user experience is improved. And good user experience is ensured.

The embodiment of the invention provides an adaptive filtering method and device, electronic equipment, a readable storage medium and a chip, and the method comprises the steps: obtaining the distance Doppler matrix data of a millimeter wave radar; determining a bottom noise threshold of at least one distance section according to the data of the plurality of continuous frames; determining the point cloud efficiency; determining an adaptive constant false alarm parameter corresponding to the current frame according to the point cloud effective rate corresponding to the historical frame; executing two-dimensional detection according to the adaptive constant false alarm parameter and the background noise threshold corresponding to the current frame, and determining an original point cloud; filtering invalid point clouds in the original point clouds corresponding to the plurality of continuous frames, and determining optimized point clouds; identifying a scene corresponding to the optimized point cloud, and determining false target features in the scene; and filtering false target features in the optimized point cloud to determine a filtered point cloud. Through the scheme of the invention, the accuracy of millimeter wave radar target detection is improved.

The invention discloses a signal insertion loss equalization method and equalization circuit. The method comprises the following steps: respectively carrying out first-stage equalization processing and second-stage equalization processing on an original input signal through a continuous time linear equalizer based on a first equalization parameter and a second equalization parameter to generate an equalized output signal; updating a second equalization parameter according to a preset linear equalization algorithm based on the equalized output signal, and performing decision feedback equalization processing on the equalized output signal through a decision feedback equalizer to obtain a feedback tap coefficient of the decision feedback equalizer; weighting the feedback tap coefficient according to a preset weight to generate a weighted coefficient; and comparing the weighted coefficient with a preset noise threshold, and updating the first equalization parameter according to a preset first strategy or a preset second strategy. According to the invention, the problem of over-equalization caused by taking the second-stage equalization value as the first-stage equalization value in the equalization architecture of the joint equalization signal of the decision feedback equalizer and the continuous time linear equalizer is solved.

A reflective device that greatly enhances the detectability and signal processing capabilities of object detection sensors to detect, recognize, classify, and track small aspect ratio targets like cyclists, pedestrians, and other vulnerable road users (VRU's). Enhanced object detection is achieved by the application of a novel hybrid reflective surface where prismatic and metalized materials have been altered into a composite and affixed to a specified geometric surface that optimizes the quality and quantity of raw object detection signal data obtained from individual sensors and the collective group of sensors when the data is fused. It is the simultaneous optimization of the raw signal data being transmitted from each of the sensor modalities (radar, camera-vision, and lidar) through the enhanced illumination and reflectivity techniques and materials described above that produces the increased Signal-to-Noise ratio that elevates the visibility of the target object well above the noise threshold to appear on the relevant object list of the collision avoidance system.