745 results about "Filter (signal processing)" patented technology

A system and method are disclosed for low-light image enhancement using hierarchical adaptive wavelet decomposition with cross-scale feature fusion. The system analyzes a raw input image to determine image characteristics and preprocessing parameters. A hierarchical adaptive wavelet decomposition process creates a variable-depth decomposition tree comprising frequency domain nodes, with decomposition depth determined by local image complexity. Cross-scale feature fusion implements attention mechanisms between nodes at different decomposition levels, enabling bidirectional information flow across scales. A dynamic network pool allocates specialized neural networks to process nodes based on their frequency characteristics, with weight sharing between similar nodes for efficiency. An adaptive reconstruction engine traverses the decomposition tree using learned filters and multi-scale residual learning to produce an enhanced image. The hierarchical approach enables superior low-light image enhancement by allocating computational resources based on content complexity, achieving better quality than fixed decomposition methods while maintaining compatibility with existing image signal processing pipelines.

The invention belongs to the technical field of underwater acoustic engineering and digital signal processing, and particularly relates to a fractional delay FIR (Finite Impulse Response) phase calibration method and system of a multichannel sonar system. Comprising the steps of signal acquisition and reference channel selection; high-precision relative delay estimation; calculating a cross-correlation function of other channel signals and the reference channel signal, performing coarse estimation by searching a peak point of the amplitude of the cross-correlation function, and performing fine estimation on the peak position by using a parabola interpolation method to obtain the delay time of each channel relative to the reference channel; designing an FIR fractional delay filter; digital filtering and phase calibration; verifying a calibration effect; and calculating the phase of each channel signal at the target frequency point after calibration, and counting the standard deviation of each channel signal so as to evaluate the improvement degree of phase consistency. The method aims at overcoming the defect that traditional integral multiple sampling delay correction precision is insufficient, high-precision phase compensation of a sub-sampling point level is achieved, and therefore the performance of algorithms such as beam forming of a multi-channel sonar system is remarkably improved.

The invention discloses a self-adaptive rotating baseline direction finding method, device and equipment, a medium and a terminal. Signals are continuously collected through the base line rotatable antenna array; rapidly identifying and outputting environment parameters by using the trained environment evaluation model, and evaluating the environment grade; constructing a dynamic direction-finding angle model by combining the attitude parameters and the motion parameters of the mobile platform, the control parameters of the antenna array and the environmental parameters; according to the environment parameters and the environment grades, a dynamic parameter optimization rule is formulated, and control parameters, direction-finding resolving parameters and signal processing algorithm parameters of the antenna array are adjusted; and based on the environmental parameters, the adjusted control parameters of the antenna array, the adjusted direction-finding resolving parameters and the adjusted adaptive filter parameters, calculating an incoming wave angle by using a dynamic direction-finding angle model. According to the method, high-precision incoming wave signal direction finding is realized in a dynamic environment, and the method is suitable for mobile scenes such as unmanned aerial vehicles and vehicle-mounted communication.

The invention belongs to the technical field of intelligent wireless sensing and radar signal processing, and particularly relates to a millimeter wave radar gesture recognition feature processing method, which is particularly suitable for scenes with environment interference (such as walking of others and static clutter), and specifically comprises the following steps: S1, preliminary filtering by a self-adaptive filter; s2, carrying out improved I CEEMDAN decomposition; s3, I MF component classification and processing; s4, signal reconstruction; the experimental result shows that the method provides a robust and efficient solution for gesture recognition, and can be widely applied to the fields of man-machine interaction, virtual reality, intelligent equipment control and the like.

The invention discloses a distribution network power line anti-interference communication method based on adaptive filtering, and belongs to the technical field of distribution network power line communication. According to the method, a communication signal adopting a frequency shift keying modulation mode is acquired from a power line coupler of a distribution network through a signal acquisition module, the communication signal is preprocessed by using a digital signal processing unit, spectral analysis is performed on the preprocessed signal, and characteristic parameters of interference noise are extracted; a coefficient vector of a finite impulse response adaptive filter is initialized based on the characteristic parameters, the order of the filter is in direct proportion to the reciprocal of the dominant interference frequency, fine adjustment is carried out based on noise energy distribution through a table look-up method or a linear mapping relation, and the weight coefficient of the filter is adjusted in real time in the communication process. The adjustment step length is dynamically adjusted according to the real-time estimated signal-to-noise ratio, and finally, the processed signal is output through the adaptive filter and data demodulation is carried out. The method is mainly used for improving the anti-interference capability and the communication reliability of the power private line communication of the distribution network.

The invention relates to the technical field of micro electro mechanical system sensors and signal processing, in particular to an acceleration sensor temperature drift compensation method and device and electronic equipment, and the method comprises the steps: obtaining the dynamic response data of an acceleration sensor at a plurality of working temperatures; fitting the dynamic response data to obtain a physical parameter and a continuous time transfer function of the acceleration sensor, and determining a digital filter coefficient according to the physical parameter and the continuous time transfer function; fitting based on the digital filter coefficient and the temperature to obtain a linear drift coefficient of the digital filter coefficient and the temperature, constructing a temperature offset compensation model according to the linear drift coefficient, inputting the working temperature of the acceleration sensor into the temperature offset compensation model, and outputting the digital filter coefficient by the compensation model, and performing temperature drift compensation on the acceleration sensor by using the digital filter coefficient. Therefore, the problems of output distortion caused by the dynamic characteristic of the acceleration sensor along with temperature drift, difficulty in realizing effective temperature self-adaptive dynamic compensation and the like are solved.

The invention relates to a time domain broadband adaptive beam forming method and system based on Chebyshev weighting, and belongs to the field of array signal processing. Aiming at the technical problems of poor real-time performance and high sidelobe of the existing broadband beam forming, the method comprises the following steps of: dividing a received broadband signal into a plurality of sub-bands, obtaining an optimal weight vector for each sub-band by adopting a minimum linear constraint iterative algorithm after down-conversion, constructing an expected response of an FIR filter according to each weight, obtaining a filter coefficient through L2 norm convex optimization, and finally obtaining a high sidelobe beam according to the expected response of the FIR filter. And performing time domain weighting on each array element signal by using a filter bank, and outputting a directional beam. According to the method, the calculated amount is low, a main lobe and interference null can be formed in real time in a broadband, and a certain side lobe height is kept.

The invention relates to the technical field of ultrasonic scanning microscopes, in particular to a system and a method for measuring surface unevenness and warping of an ultrasonic scanning microscope. The system comprises a water tank, a light emitting device, a light receiving device and a signal processing module, the light emitting device generates line laser through a semiconductor laser and an optical shaping module, and scanning is achieved through a high-precision galvanometer. The light receiving device is provided with a narrow-band filter, a telecentric lens and a CMOS sensor and is used for capturing a light spot image; the signal processing module integrates sub-pixel positioning, galvanometer nonlinear correction, self-adaptive filtering and temperature compensation algorithms, light spot center sub-pixel-level positioning is achieved through Gaussian curved surface fitting, galvanometer correction and temperature drift compensation are combined, the measurement precision and stability are improved, and finally high-precision height information is fed back to an ultrasonic scanning system. According to the invention, the accuracy and reliability of surface unevenness and warping measurement are improved.

This disclosure provides methods, devices, and systems for audio signal processing. The present implementations more specifically relate to speech enhancement techniques for separating microphone signals into speech, echo, and noise signals. In some aspects, a speech enhancement system may include a delay estimator and an acoustic echo and noise (AEN) decoupling filter. The delay estimator receives a microphone signal via a microphone and a far-end audio signal for output via a speaker and estimates a reference audio signal based on a delay between the microphone signal and the far-end audio signal. In some aspects, the AEN decoupling filter may determine a speech mask, an echo mask, and a noise mask based on the microphone signal and the reference audio signal and may suppress an echo component and a noise component of the microphone signal based on the determined set of masks.

The invention relates to the technical field of radio frequency signal processing, and discloses a digital filtering repair method and system for signal distortion, and the method comprises the steps: obtaining a frequency domain amplitude-frequency response and a phase response; constructing a phase compensation amount by adopting piecewise polynomial fitting and a phase inversion mechanism; a complex number logarithm domain mapping mechanism is adopted to execute composite frequency response inversion; constructing a switchable hybrid digital filter with an amplitude path and a phase path coupled in parallel; multi-band adaptive scheduling is executed; and outputting the radio frequency baseband signal stream. The technical problems that in the prior art, frequency response nonlinear distortion in a broadband range cannot be dealt with by adopting a fixed template or a single-path filter, and particularly, a high-precision and low-delay dynamic compensation effect cannot be realized in a scene that multi-band coupling interference exists in a radio frequency ADC channel with the bandwidth exceeding 800MHz are solved. Due to the fact that the switchable hybrid digital filter is constructed, accurate modeling and flexible recovery of distortion characteristics in broadband signals are achieved.

The invention relates to the technical field of satellite navigation and wireless communication, and discloses an indoor positioning method and system based on feeder multiplexing Beidou double-frequency, and the method comprises the steps: receiving outdoor B1I and B2a signals through a high-gain Beidou double-frequency receiving antenna, carrying out the frequency separation and signal conditioning through a double-frequency separation filter, and carrying out the positioning of the B1I and B2a signals; and transmitting the B1I signal to an indoor distributed antenna for broadcasting through the existing communication feeder network, and transmitting the B2a signal to a central directional antenna to establish a time synchronization reference. A mobile terminal receives a dual-frequency signal, capturing and tracking are carried out through digital signal processing, and pseudo-range and carrier phase observation values are extracted. And performing pairing processing on observation data of the same antenna, calculating a dual-frequency pseudo-range difference value, eliminating system errors, and performing position calculation by adopting a weighted least square method and Kalman filtering. The method solves the problem that the traditional GPS signal cannot cover the indoor environment, and has a good application prospect in the scenes of underground commercial complexes, tunnels, parking lots and the like.

The invention relates to the technical field of radar information, in particular to a ground clutter suppression method for a ground reconnaissance radar, which comprises the following steps of: firstly, establishing a clutter profile map by using echo data, judging information inside and outside a clutter according to the clutter profile map, and selecting different signal processing flows, namely, adopting a detection channel 1 outside the clutter, adopting a detection channel 2 and a detection channel 3 inside the clutter and adopting a detection channel 2 and a detection channel 3 outside the clutter; after the detection channel 1 passes through the MTD filter, clutter suppression processing is not carried out, and a detection result is output; the detection channel 2 is a coherent processing channel, firstly performs mean filtering processing, then performs coherent processing, performs clutter suppression processing through phasor mean filtering, and outputs a detection result; and the detection channel 3 is a zero Doppler processing channel and is used for detecting a low-speed target in a clutter area, compared with the prior art, the method can reduce Doppler sidelobes as much as possible on the premise of ensuring that the ground clutter height is suppressed, and has the minimum main lobe width and the minimum signal-to-noise ratio loss.

The invention provides a control system for suppressing peak of output voltage and current of a power amplifier. The system comprises a PS signal processing module, a PL signal processing module and a high-voltage power circuit, wherein the PS is configured to receive a bus signal issued by an upper computer, execute digital Gaussian filtering processing on the bus signal and then transmit the bus signal to the PL signal processing module; meanwhile, relevant data of the power amplifier are collected and uploaded; the PL signal processing module is configured to receive a signal which is issued by the PS and is subjected to digital Gaussian filtering processing, and pre-process the signal; and transmitting the processed signal to a high-voltage power circuit to control the high-voltage power circuit to execute power conversion operation on the load. According to the method provided by the invention, smooth transition is realized at the phase jump position of the signal by adjusting the parameters of the digital Gaussian filter, so that the peak of the output voltage and current of the power amplifier is inhibited, the stress of a post-stage high-voltage power circuit device is reduced, the post-stage output power is effectively improved, and the stability of the power amplifier is improved.

A measurement and control simulation device based on a measurement and control data transmission integrated system comprises an upper computer display control test module, a PC host module, a signal processing master controller module, an isolation DC / DC module, a down-conversion module, a filtering module, an isolator module and an outer end face interface module. The system has the characteristics of multiple modulation systems, a spread spectrum function, controllable output power, Doppler frequency change and the like, can be used for simulating a star chain control system link test in a ground test system, and fully improves the index assessment performance during system docking; meanwhile, the design of a down-conversion link meets the requirements for the strength and sensitivity of the received signal, the stability and accuracy of the radio-frequency signal after frequency conversion in a low-power injection state are remarkably improved, and a new scheme is provided for a high-frequency conversion mode. Besides, the display control module of the equipment has the functions of multiplexing, reconstruction, multi-data interaction and the like, so that multifunctional and multi-task full-system test coverage can be realized, the cost investment of test systems such as spacecrafts and the like is greatly reduced, and the multifunctional index test coverage efficiency is improved.

The utility model relates to the technical field of satellite navigation, in particular to a satellite navigation anti-interference signal intensifier, which comprises a receiving antenna, a prefilter, a fixed amplification module and an automatic gain module which are sequentially connected, the output end of the fixed amplification module is further connected with a control module, and the control module comprises a peak value detection unit and a switch control unit. Two output ends of the switch control unit are connected with a control end of the automatic gain module, the peak detection unit is used for detecting a signal peak value, and the switch control unit controls the amplification factor of the automatic gain module based on the signal peak value output by the peak detection unit. According to the utility model, the prefilter is used for filtering interference signals, then the peak value detection unit is used for judging the magnitude of the signals, and then the switch control unit is used for selecting different resistors, so that the amplification factor of the automatic gain module is changed, the signals are enhanced, the final signals are in a proper range, subsequent signal processing is facilitated, and the practicability is higher.

The invention relates to the technical field of amplifiers, and discloses an analog-to-digital converter combination instrument amplifier which comprises a first-stage amplifier, the first-stage amplifier is in signal connection with a second-stage amplifier, the second-stage amplifier is in signal connection with a front-end low-pass filter (LPF), the front-end low-pass filter (LPF) is in signal connection with an analog-to-digital converter (ADC), and the analog-to-digital converter (ADC) is in signal connection with the analog-to-digital converter. And an unbalanced input-to-balanced differential circuit output module is arranged between the second-stage amplifier signal and a front-end low-pass filter (LPF). From the perspective of signal processing and conversion, a precise signal transition bridge is constructed by adding an unbalanced input-to-balanced differential circuit output module, unbalanced signals output by a second-stage amplifier are converted into double-end balanced differential signals, common-mode noise interference is effectively resisted through a differential transmission mode, the signal purity is guaranteed, and the signal quality is improved. The front-end low-pass filter and the analog-to-digital converter are adaptive to differential signals, so that the signal transmission is stable and anti-interference, and the analog-to-digital conversion is more accurate.

The invention discloses a dynamic self-triggering filtering method under incomplete semi-Markov kernel information, relates to the technical field of automatic control and signal processing, and aims to solve the problems that full acquisition of semi-Markov kernel information is difficult, communication burden is heavy and peak control is insufficient. A self-triggering mechanism containing a dynamic variable is designed to determine a data transmission moment by classifying a known / unknown set of semi-Markov information and utilizing known parameters and an unknown lower bound, a modal-dependent filter is constructed, and the mean square index stability and robust performance of a filtering error system are verified in combination with the Lyapunov theory and a linear matrix inequality technology. The problems that an existing method is high in conservative property and wastes resources are solved.

The invention relates to the field of voice signal processing and voice recognition, and discloses a voice recognition enhancement method and system based on harmonic model fundamental frequency optimization and RNN noise suppression, and the method comprises the steps: collecting a voice signal in a noise environment in real time, carrying out the framing and windowing of the voice signal, and generating multi-dimensional time-frequency data; estimating the fundamental frequency of each frame of voice through a cepstrum analysis method, and screening effective fundamental frequency frames according to a confidence coefficient threshold to form a fundamental frequency characteristic matrix; dynamically adjusting the noise power spectrum of the Wiener filter under the drive of the fundamental frequency characteristic matrix, and carrying out dislocation fusion on the filtering output and the original spectrum to form an enhanced spectrum first draft; inputting the enhanced spectrum first draft into a recurrent neural network in a framing manner, predicting the gain of each frequency band, calculating an inhibition factor, and generating a multi-frame continuous enhanced spectrum sequence; multiple frames of continuous enhanced spectrum sequences are synthesized into voice signals through inverse short-time Fourier transform, an end-to-end enhanced recognition process is formed, and the method has the advantage of improving accuracy.

The invention relates to the technical field of power system monitoring, discloses an anti-harmonic PT current monitoring system and method, and aims to solve the problem of secondary side current signal distortion of a voltage transformer caused by power grid harmonic pollution in the prior art. The method comprises the steps of electrifying and initializing a system, starting a high-speed analog-to-digital converter to acquire a voltage signal, executing fast Fourier transform to identify dominant harmonic waves, calculating and configuring a capacitance value of a tunable LC trap unit to suppress specific harmonic waves, and finally outputting a high-fidelity analog voltage signal in direct proportion to fundamental current. The system comprises a current-voltage conversion module, a tunable LC notch filter array, a high-speed analog-to-digital converter, a digital signal processing unit and a microcontroller. According to the technical scheme, dynamic self-adaptive suppression and precise selective harmonic wave blocking of power grid harmonic waves can be realized, low delay and high fidelity characteristics are guaranteed, and the engineering practicability and reliability of the system are improved.

The invention discloses a dynamic reconfigurable signal processing platform based on a ZYNQ architecture, and belongs to the technical field of digital signal processing, and the dynamic reconfigurable signal processing platform comprises a channel preprocessing unit, a high-speed AD sampling unit, a ZYNQ-PL logic unit and a ZYNQ-PS algorithm processing unit. A radio frequency signal is fed in from an antenna end and then enters the channel preprocessing unit, a balun circuit and a filter bank are adopted to carry out preselection filtering, amplification and conditioning on the radio frequency signal, and the signal is extracted and sent to the high-speed AD sampling unit; the high-speed AD acquisition unit converts a received analog signal into a digital signal and transmits the digital signal to the ZYNQ-PL logic unit, and the ZYNQ-PL logic unit is connected with the ZYNQ-PS algorithm processing unit through an AXI bus; wherein the ZYNQ-PL logic unit is composed of a static region and three dynamic regions, and is mainly used for realizing a logic part of a functional waveform and completing reconstruction and loading of the functional waveform; and the ZYNQ-PS algorithm processing unit completes algorithm processing, realizes modulation and demodulation of a functional waveform and realizes a functional algorithm.

The embodiment of the invention provides a system and method for online measurement of the slag state in electric arc furnace steelmaking, and relates to the field of steelmaking, the system comprises a front-end audio acquisition unit, a signal processing unit, a video splashing detection unit and a picture debugging display unit, the front-end audio acquisition unit is used for acquiring a noise signal in a furnace, and the signal processing unit is used for processing the noise signal; the signal processing unit is used for carrying out frequency division processing on the received noise signal, outputting a standard signal and obtaining a voiceprint slagging curve based on the standard signal, the video splashing detection unit comprises a video filtering camera and a video acquisition card and is used for acquiring an electric furnace mouth image picture, and the picture debugging display unit is used for displaying the electric furnace mouth image picture. The method is used for displaying the voiceprint slagging curve and the electric furnace mouth image. Intelligent measurement and control of the slag state in the steelmaking process of the electric arc furnace are achieved, manual intervention is reduced, the steelmaking efficiency and the molten steel quality are improved, the production cost is reduced, and wide application prospects are achieved.

The invention provides an electric power meter data real-time analysis and abnormity early warning method based on edge calculation, and belongs to the technical field of data analysis and early warning, and the method comprises the steps: collecting the multi-modal data of an electric power meter based on a multi-channel analog-to-digital converter, employing a hardware filter circuit to eliminate high-frequency noise, and obtaining the data of the electric power meter; signal gain self-adaptive adjustment is carried out based on a reconfigurable amplifier; a digital signal processing accelerator is used to carry out Fourier transform on a matrix constructed by the standardized data stream, and a multi-core processor is combined to carry out analysis to generate a feature vector; the method comprises the following steps: acquiring environmental parameters in real time based on an environmental sensor, dynamically adjusting an anomaly detection threshold in combination with a machine learning model trained by historical data, and comparing a feature vector with the dynamic threshold to generate an anomaly signal; the relay control circuit triggers sound-light alarm, the physically isolated communication module sends an early warning instruction to the cloud platform, and meanwhile, the redundant power supply module is started to control the electric power meter to operate continuously. And the efficiency and accuracy of subsequent abnormity early warning are improved.

The invention provides a magnetic suspension platform deformation monitoring system and method, and the system comprises Hall sensor arrays which are uniformly disposed at the edge and supporting points of a magnetic suspension motion platform, and are used for detecting the magnetic field intensity of the position where the magnetic suspension motion platform is located, and generating an original analog signal; the signal processing module is connected with the Hall sensor array, performs filtering, amplification and analog-to-digital conversion on the original analog signal, and outputs digital magnetic field data; the data analysis unit is connected with the signal processing module to receive the digital magnetic field data, and magnetic field intensity change is converted into deformation quantity of the magnetic suspension platform through a preset algorithm model; and the feedback control unit is connected with the data analysis unit and a control system of the magnetic suspension motion platform, generates a control instruction according to the deformation quantity, and adjusts the electromagnetic force of the magnetic suspension motion platform to correct the pose. Deformation of the magnetic suspension platform can be accurately monitored in real time, the pose can be corrected in time, and stable operation of the magnetic suspension platform is guaranteed.

The invention relates to the technical field of radar signal processing, in particular to an urban environment low, small and slow target radar clutter suppression method, which comprises the following steps of: 1, acquiring and decomposing a signal; step 2, adaptive clutter cancellation; step 3, space-time combined treatment; step 4, constant false alarm rate detection; step 5, fine classification and identification; step 6, target tracking and early warning; according to the method, a cascade processing framework integrating multi-scale signal decomposition, adaptive filtering, space-time combined processing and intelligent identification is constructed, so that the defect that the performance of a traditional method is sharply reduced in a city strong non-uniform and non-stationary clutter environment is effectively overcome; and in combination with a recursive least square filter with dynamically adjustable parameters, the combined suppression capability of static ground clutter and dynamic traffic interference is remarkably improved, so that the detection of a'low, small and slow 'target under the condition of an extremely low signal-to-clutter ratio becomes possible.

The invention discloses a coupling pulse distortion compensation method for superconducting quantum computing, and relates to the field of signal processing, and the method comprises the steps: S1, inputting an initial square wave signal into a first IIR filter, and reducing the frequency attenuation of superconducting quantum bits; s2, outputting the initial square wave signal to a second IIR filter to improve the high-frequency component of the initial square wave signal; s3, outputting the initial square wave signal to a third IIR filter to eliminate pulse back edge reflection of the initial square wave signal; and S4, outputting the initial square wave signal to a first FIR filter to carry out ripple correction so as to complete pre-distortion correction. By setting the staged pre-distortion compensation of the three-section IIR filter and the one-section FIR filter, the pre-distortion compensation of the square wave signal is more accurate and stable, the square wave edge response is rapid and the amplitude is correct, and the time delay and the amplitude error caused by the link are reduced; the quantum bit Z-axis phase control method has the advantages that quantum bit Z-axis phase control is more accurate, and the fidelity of a square wave signal gate is prevented from being reduced.

A digital signal processing method is for enhancing fidelity of equivalent-time waveform measurements. The method includes receiving a digitized equivalent-time waveform of a repeating signal under test (SUT), applying a low-pass filter to the digitized equivalent-time waveform to obtain a smoothed waveform, generating a residual waveform by subtracting the smoothed waveform from the digitized equivalent-time waveform, estimating contributions of multiple noise sources in the residual waveform using a regression model, computing target noise and jitter values by removing known intrinsic contributions, and reconstructing a corrected waveform by combining the smoothed waveform with a scaled version of the residual waveform, wherein the scaling is based on the target noise source contributions.

The invention discloses a digital signal processing method and system based on an FPGA, relates to the field of digital signal processing, and introduces a staged variable bandwidth CDR strategy. In the initial stage, the signal frequency offset is quickly estimated through feedforward frequency analysis, and a high-bandwidth loop is started on the basis of the signal frequency offset, so that top-speed locking is realized, and the requirements of production testing and other scenes on efficiency are met. When the system confirms that locking is stable through hardware logic, a multi-step interpolation state machine is triggered, the state machine can smoothly switch the coefficient of the loop filter from a high bandwidth mode to a low bandwidth mode without disturbance, and the lock losing risk in the switching process is avoided. Finally, in a stable low-bandwidth mode, the system can perform accurate jitter decomposition and data analysis by using a high-precision recovery clock. In this way, the two modes of rapid capture and high-precision measurement are fused in one operation process, and the static design limitation in the prior art is solved.

The invention relates to the technical field of space environment detection, in particular to a photoelectric sensor for space dust particle size detection, which comprises an optical signal collection assembly and an electric signal conversion and acquisition assembly, and is characterized in that the optical signal collection assembly comprises a support, a front pressing plate, an optical filter and a sensor; the electric signal conversion and acquisition assembly comprises a circuit box body, a photoelectric conversion detector, a signal processing circuit board, a signal wire passing sleeve and a circuit box cover. The support of the particle size sensor is used as a main structure, and other structures are subjected to split design and integrated precision assembly, so that the processing difficulty of a complex structure is reduced, the machining precision of a single structure is effectively improved, and the form and position processing error of each structural part is effectively controlled; the non-imaging compound paraboloid condensation sensor is independently designed and processed, so that the processing precision of a product is improved; and vibration reduction design is independently carried out on internal structural components, so that the mechanical impact resistance of weak parts is improved.

The invention discloses a real-time self-adaptive electroencephalogram artifact suppression and enhancement embedded system. The system aims at overcoming the limitation of an existing portable EEG device in the aspect of artifact processing, various artifacts in EEG signals are recognized and removed in a low-power-consumption, high-precision and real-time mode, and meanwhile the quality of effective EEG signals is optimized and enhanced. One key innovation of the invention lies in breaking through the limitation of single EEG signal processing, and accurate separation and correction of artifacts are carried out through the assistance of EOG and EMG. For example, the EOG signal is used for assisting eye movement artifact removal through synchronous correlation analysis and an adaptive regression filter; the EMG signal is used for assisting myoelectricity artifact correction, and suppression is carried out through spectral analysis and dynamic adjustment of filter parameters. In addition, the system also has the functions of real-time detection and repair of electrode artifacts. According to the system, high-quality EEG signals close to offline processing are provided on portable embedded equipment with limited resources, and the system has universality and high-precision application potential and can be widely applied to a plurality of frontier fields such as medical diagnosis, brain-computer interface (BCI), cognitive ability enhancement, neurological rehabilitation training, sleep disorder monitoring and human-computer interaction.

The embodiment of the invention provides an ultrasonic distance measurement chip, an ultrasonic distance measurement device and a self-adaptive threshold generation method. The ultrasonic ranging chip comprises an echo signal processing module, a near-field threshold generator and a near-field decision device, and the echo signal processing module is configured to receive a target echo signal generated by an ultrasonic transducer and generate a near-field echo envelope signal based on the target echo signal; the near-field threshold generator includes a filter configured to obtain a model configuration parameter for the filter, generate an adaptive threshold using the filter based on near-field echo envelope signal prediction, where a gain of the filter is adaptively adjusted based on the model configuration parameter and the near-field echo envelope signal; the near-field decision device is configured to generate first alarm information according to the near-field echo envelope signal and an adaptive threshold. According to the embodiment of the invention, self-adaptive threshold generation during near-field target detection is realized, the false alarm rate and the missed alarm rate of the decision device are reduced, and accurate detection of the near-field target is realized.