126 results about "Drift error" patented technology

The invention relates to the technical field of industrial automation control, in particular to a container liquid level measurement method, system and equipment of a pressure sensor and a medium, and provides a method for eliminating gas phase pressure influence based on a double-sensor differential measurement mechanism and dynamically correcting liquid density and sensor drift errors in combination with a temperature compensation model. The temperature data are linked in real time through a three-dimensional compensation function, density calculation and drift correction are synchronously adjusted, and multi-parameter dynamic decoupling and self-adaptive compensation are achieved; a collaborative measurement mechanism is adopted to integrate bottom and top sensor data, and a built-in temperature probe and a preset threshold are combined to complete multi-source signal fusion and compensation calculation; a dynamic calibration method is designed, and system errors are eliminated through reference pressure point calibration and structure coefficient correction; constructing a closed-loop signal processing flow, and integrating high-precision analog-to-digital conversion, digital filtering and real-time algorithm to output a compensated liquid level value; the method improves the measurement precision and stability, and is suitable for temperature change, gas phase pressure fluctuation and multi-medium scenes.

The invention discloses an error correction system and method for marine environment observation data. The error correction system comprises a data acquisition module, a compensation modeling module, an error analysis module, a data compensation module, a data fusion module and a feedback optimization module. The data acquisition module acquires ADCP flow measurement, GPS, IMU, temperature, pressure and water quality monitoring data. And the error analysis module detects a drift error by using Kalman filtering and a hidden Markov model, and analyzes an environmental error based on a long short-term memory network. The data compensation module optimizes a compensation model and improves data precision. And the data fusion module fuses multi-sensor data by adopting a particle filter and a Bayesian optimization algorithm. The feedback optimization module dynamically adjusts the weight of the compensation model according to the error correction data, and improves the adaptability of the system. According to the invention, the accuracy of ocean current monitoring data is improved, and more reliable data support is provided for underwater environment research.

The invention discloses a displacement auxiliary measuring mechanism and a reservoir dam monitoring and early warning system thereof, and belongs to the technical field of dam monitoring. The reservoir dam monitoring and early warning system comprises a data acquisition module, an attitude calibration module, a data fusion judgment module, a risk grading analysis module and a remote early warning trigger module. The distance measurement precision under the complex field condition is remarkably improved, the current mechanical direction and the reference direction are fused, a correction vector pointing to a target reflection point is generated, the direction drift error is effectively eliminated, and the distance measurement accuracy is improved by constructing a double-path model of main path fusion and auxiliary path comparison. According to the method, non-structural anomalies caused by sensor body interference or environmental disturbance are eliminated, data offset is corrected in real time, a stable trend curve is output, when a main path has a drift or error trend, the main path is automatically guided to converge to an auxiliary path, and the abnormal data recognition and restoration capability is enhanced.

The invention discloses an automatic driving control method and system based on multi-source data aggregation, and particularly relates to the technical field of automatic driving. The method comprises the following steps: acquiring sensor data, extracting an instantaneous relative frequency drift feature and a sensor data fusion drift error feature, evaluating the accuracy of sensor data time synchronization based on an adaptive weighted fusion algorithm, and dynamically adjusting the confidence coefficient weight of each piece of sensor data. The recurrent neural network is used for predicting the future movement track of the obstacle on the data with high time synchronization accuracy, in addition, through a confidence feedback mechanism, the sensor time synchronization accuracy and the environment perception data quality are combined, the data fusion error is dynamically corrected, the control precision and the driving stability are improved, and the driving stability is improved. According to the method, the problem of data mismatching caused by time synchronization errors can be effectively reduced, the sensing accuracy, trajectory prediction capability and safety of an automatic driving system are improved, and the vehicle has more stable and intelligent decision-making capability in a complex traffic environment.

The invention provides an IGBT junction temperature prediction method and system based on dynamic thermal impedance correction. The method comprises the following steps: acquiring temperature data in real time, reversely deducing IGBT loss in combination with a pre-constructed thermal network model, and storing the IGBT loss in historical data; obtaining an IGBT loss average value under the same working condition, and calculating a difference value between the IGBT loss average value and the IGBT loss and a specific value of the IGBT loss average value to obtain a loss offset coefficient; judging whether the loss deviation coefficient is continuously greater than a preset value in a continuous period, if so, judging that the heat-conducting silicone grease is aged, calculating an aging coefficient through loss data and temperature data in the continuous period, and correcting the thermal network model by adopting the aging coefficient; and obtaining the corrected internal transient thermal impedance of the IGBT and the loss of the IGBT, and further predicting the junction temperature of the IGBT. According to the method, the thermal network model is adopted to reversely deduce the real-time loss power of the IGBT, and electric parameter drift errors are avoided; and a dynamic thermal impedance correction mechanism is introduced to ensure long-term accuracy of junction temperature prediction.

The invention discloses a high-precision Beidou satellite navigation and positioning data acquisition method and system, particularly relates to the technical field of satellite navigation and positioning processing, and is used for solving the problem of positioning error increase caused by receiver hardware delay drift in the prior art. Inverting the first dynamic reference value by using carrier phase integral displacement, and extracting a third-order intermodulation component through coherent demodulation to generate a second dynamic reference value; adopting mutual information entropy analysis to select an effective reference value to calculate a residual error; fitting a theoretical value according to the carrier phase change rate to calculate deviation; marking a hardware drift error when the time domain correlation continuously exceeds a threshold value; finally, the ionosphere residual error is dynamically compensated to generate a corrected observation value, effective separation of the hardware drift error and the ionosphere residual error is realized, and the precision and reliability of long-time observation in a dynamic environment are improved.

The invention relates to the technical field of drainage control, in particular to a liquid level sensing drainage control method and system based on electronic and floating ball cooperative detection, and the method comprises the steps: fusing the angular displacement, capacitance value and acceleration disturbance data of a floating ball, and constructing a liquid level state observer; a dynamic compensation factor is introduced to strip liquid shaking interference, and an accurate liquid level reference value is obtained; a composite control vector is constructed based on the liquid level deviation and the change rate, and a drainage instruction is generated through analysis to control a valve to act; meanwhile, a self-adaptive feedback adjustment mechanism is established, observer parameters are dynamically calibrated through liquid level response residual errors, and the drifting error of an actuator is offset; according to the technical scheme, the robustness of drainage control can be remarkably improved.

The invention discloses a pressure gauge temperature data processing method based on temperature calibration drift error compensation, and relates to the field of data processing, and the method comprises the steps of dynamic temperature drift compensation preprocessing, adaptive noise filtering and feature enhancement, pressure gauge temperature data modeling and the like. Dynamic temperature drift compensation is achieved, and the problem that temperature change and fault mutation cannot be distinguished through traditional static linear transformation is solved; noise interference is suppressed, potential fault features are reserved, and expression of key abnormal points is enhanced. The response capability to sudden faults is effectively improved; temperature drift and fault features are effectively decoupled, it is ensured that the network does not depend on specific temperature conditions, and the adaptability of the model to different temperature scenes is enhanced; the accuracy of fault prediction is improved, and prediction errors caused by temperature changes are reduced.

The invention provides an anti-cracking performance evaluation method and system based on a concrete shrinkage rate. The method comprises the following steps: firstly, collecting shrinkage rate real-time sequence data and an acoustic emission signal flow of a concrete sample in a curing process, separating a high-frequency elastic wave energy attenuation characteristic value from the acoustic emission signal flow, and carrying out space-time coupling on the high-frequency elastic wave energy attenuation characteristic value and a shrinkage rate jump point in the shrinkage rate real-time sequence data to generate a crack initiation tendency index; then obtaining a calibrated crack initiation tendency index based on an ambient temperature hysteresis effect and a temperature drift error of the calibrated crack initiation tendency index, and then outputting an anti-crack performance grade according to a grading deviation degree between a pre-designed grading parameter and a fluctuation range of the calibrated crack initiation tendency index; according to the technical scheme provided by the invention, the essential defect that a traditional method cannot correlate material characteristics with environmental response is overcome, direct quantitative mapping of material structure performance and damage evolution is also realized, and a traceable material-level basis is provided for engineering anti-crack design.

The invention discloses a wire state monitoring method and system based on adaptive Kalman filtering. The method comprises the following steps: acquiring first parameter information, and performing first prediction according to the first parameter information; acquiring second parameter information, and calculating a first target coefficient according to the second parameter information; and updating the result of the first prediction according to the first target coefficient, and monitoring the wire state according to the updated result. By adopting the adaptive Kalman filtering technology, the method can effectively combine the data of the GNSS sensor and the IMU sensor so as to improve the precision and reliability of wire state monitoring. In a dynamically changing environment, a GNSS signal may be interfered, and an IMU sensor may generate a drift error. According to the invention, the filtering parameters can be dynamically adjusted through the adaptive Kalman filtering algorithm, so that accurate lead state estimation can be provided in different environments.

The invention relates to the technical field of ultra-precision intelligent manufacturing, in particular to an ultra-precision machining error compensation method based on multi-modal information fusion, a medium and equipment. The method comprises the following steps: acquiring three-dimensional shape data of a workpiece through an in-situ measurement device, synchronously acquiring temperature field and vibration data, constructing a multi-modal space-time tensor, inputting a physical information neural network to decouple a static geometric error, a time-varying thermal drift error and a dynamic vibration error, and generating a four-dimensional correction tool path to realize reverse compensation. According to the method, physical constraints are embedded through a PINN model, the problem of false thermal drift misjudgment in a traditional method is solved, experiments show that the RMS error of free-form surface machining is reduced to 5 nm or below, and the precision is improved by 70% or above; and meanwhile, error decoupling is endowed with physical interpretability, the small sample generalization ability is enhanced, and a technical basis is provided for process optimization.

The invention provides an intelligent swing arm adjusting and detecting system for automobile driving. The intelligent swing arm adjusting and detecting system comprises a multi-source sensing module used for collecting vibration signals, stress distribution and displacement data of a swing arm in real time; the attitude resolving module receives the sensing data and constructs a three-dimensional dynamic swing arm model; the dynamic compensation module calculates attitude deviation based on the model and generates compensation parameters; the execution mechanism module drives the swing arm to adjust according to the compensation parameters; the abnormity diagnosis module analyzes the dynamic response spectrum to determine the fault type; the self-calibration module corrects the drift error of the multi-source sensing data; the control output module integrates the compensation parameter and the diagnosis result to generate a control signal. The stability and reliability of the automobile driving system can be improved, the maintenance cost is reduced, and the breakdown time is shortened.

The invention discloses a differential processing algorithm for laser pulse ranging echoes, which is characterized in that the echoes of laser pulse signals are differentiated through a mathematical method, so that an extreme point, namely the peak moment of the echoes, is solved. According to the differential processing algorithm of the laser pulse ranging echo, the extreme point is obtained by differentiating the Gaussian signal of the time t. The change of the intensity of the echo does not cause the change of the extreme point moment, i.e., the t0 moment is not changed, so that the method fundamentally eliminates the moment discrimination error delta t of the leading edge discrimination method, naturally does not need to be optimized to obtain the dual-threshold leading edge discrimination method, and also avoids the problems of other methods in use. When the echo size changes, the peak moment can still be accurately identified, the drift error is greatly eliminated, in the pulse laser ranging echo moment identification method, the accuracy is far higher than that of other methods, linear fitting and other secondary error compensation are not needed, the engineering complexity is reduced, the workload is reduced, and the adaptability is improved.

The invention discloses an inertial navigation system point position correction method and device based on a transverse geography system, and the method comprises the steps: obtaining transverse longitude and latitude calculated by inertial navigation updating and angle measurement information measured by a gyroscope at the current navigation time, building a transverse geography system navigation drift error model, in combination with a conversion relation between navigation parameters of a transverse geographic coordinate system and a traditional geographic coordinate system, a navigation drift error compensation parameter is calculated through a transverse longitude error and a transverse latitude error, and the transverse longitude of inertial navigation update calculation and the transverse latitude of inertial navigation update calculation are corrected; the corrected transverse longitude and the corrected transverse latitude are obtained, navigation drift error compensation parameters are projected to a transverse geographic coordinate system, angle measurement information measured by a gyroscope is corrected, and corrected angle measurement information is obtained. According to the method, the inertial navigation high-latitude long-endurance navigation precision can be improved based on position correction and drift error suppression of high-latitude transverse geographical system long-endurance navigation.

The invention discloses an intelligent oven temperature regulation and control system and method based on a self-adaptive control method, and the method comprises the steps: collecting first temperature data in an oven based on sensors, and obtaining a redundancy check temperature value through a redundancy check method based on multiple temperature sensors; calculating a current temperature drift error value according to the redundancy check temperature value, inputting the temperature drift error value and historical drift trend data into a temperature drift prediction model, and outputting a predicted temperature drift compensation value; fusing the redundancy check temperature value with the predicted temperature drift compensation value to generate a first fused temperature value; calculating a temperature stability index in the oven based on the first fusion temperature value; based on the temperature stability index and a preset temperature fluctuation target range, the heating power of the oven is adjusted through an adaptive frequency heating control algorithm; and second temperature data in the oven are collected again, and cross validation is carried out on the second temperature data and the first fusion temperature value so as to correct the historical drift trend data.

According to the flow control system and method for the filter element flow resistance performance test provided by the invention, the self-adaptive PID control closed loop taking the real-time flow resistance coefficient as the core feedback quantity is constructed, and the high-precision sensing network and the intelligent decision algorithm are integrated; the defect that traditional manual or simple PID control is difficult to adapt to filter element characteristic change and environmental interference is successfully overcome; specifically, the system dynamically collects flow, pressure difference and temperature signals and calculates the flow resistance coefficient of a filter element in real time, PID control parameters (proportion, integration and differential terms) are adjusted in a self-adaptive mode according to the flow resistance coefficient, meanwhile, the reference value of a sensor is periodically calibrated so as to eliminate drift errors, and an electric control valve is driven to rapidly and accurately respond; according to the method, the dynamic stability and static precision of flow control are remarkably improved, multi-source interference such as pipeline pressure pulsation and fluid temperature change is effectively compensated, the steady-state error of the test flow is greatly reduced, and finally the efficient and high-precision automatic test of the flow resistance performance of the filter element is achieved.

The invention relates to a multi-fault real-time early warning system for a power distribution cabinet, and relates to the technical field of power distribution cabinet detection. Partial discharge, mechanical vibration, insulation dielectric loss and environmental parameters are synchronously acquired through a distributed sensor array; performing electromagnetic interference filtering and wavelet noise reduction preprocessing on the original data, and extracting the characteristics of pulse frequency, vibration kurtosis, dielectric loss change rate and the like; a'rule base + random forest 'mixed model is adopted to identify fault types and confidence; fault positioning with the precision of + / -3cm is realized based on sensor delay inequality and a triangulation positioning algorithm, and fault components are determined in combination with a component topology mapping table; early warning levels are divided according to fault types, confidence coefficients and component importance, and customized reports are dynamically pushed; a standard signal is injected every 24 hours to generate a compensation coefficient, and the drift error of the sensor is corrected in real time.

The invention discloses a hydraulic support attitude sensing method, device and equipment and a medium, and relates to the technical field of hydraulic support regulation, and the method comprises the steps: obtaining the relative attitude angles of a top beam and a shield beam relative to a base under a target coordinate system, and obtaining the absolute attitude angles of the top beam, the shield beam and the base under a geographic coordinate system; fusing the relative attitude angle and the absolute attitude angle to obtain attitude angles of the top beam and the shield beam; according to the method, the absolute attitude angles of the top beam, the shield beam and the base are obtained by using a complementary filtering algorithm under the condition of reducing noise interference, and the relative attitude angles and the absolute attitude angles are fused by using extended Kalman filter (EKF), so that the drift error of the IMU technology during attitude sensing of the hydraulic support is offset, and the attitude sensing accuracy of the hydraulic support is improved. And accurate attitude angles of the top beam and the shield beam of the hydraulic support are obtained.

The invention discloses a charging pile remote monitoring method and system based on an error model, and the method employs multi-axis dynamic bifurcation mapping and rotation residual aggregation to construct an error model based on multi-dimensional operation parameters, and can effectively capture the coupling characteristics of a drift error and a transient disturbance error through multi-axis disturbance bifurcation mapping. The method is more sensitive to complex fault response in actual operation, has higher multi-dimensional fitting capability and error generalization capability compared with a traditional method, can simulate periodic response offset of various operating parameters under different disturbance frequencies through rotation residual aggregation, generates stable error signals with definite directivity, and has the advantages of being high in accuracy and high in reliability. According to the method, dynamic prediction and guiding correction of the error trend can be achieved through the built error model, overfitting and error overcompensation are effectively avoided, accurate correction of the multi-dimensional operation parameters of the charging pile is achieved, and the judgment accuracy and response efficiency of remote monitoring of the charging pile are greatly improved.

The invention discloses a low-voltage alternating-current power distribution network electric leakage fault detection method and system, relates to the technical field of power grid fault detection, and is used for solving the problem of detection lag caused by incapability of timely detection when electric leakage current is relatively small but continuously exists. For each pre-selected node, acquiring and synthesizing a safety distance coefficient and a sensor compatibility ratio of each pre-selected node to obtain a key point location, acquiring the key point location and accessing a sensor of the corresponding point location, performing power-on detection to obtain a drift error and a direct current component, substituting the drift error and the direct current component into a logistic regression algorithm to obtain a sensor screening coefficient, and performing sensor screening; a sensor screening threshold is obtained through binary recursion, reserved sensors and deleted sensors are obtained, the temperature difference between the environment of each reserved sensor and the surface of a line and the total harmonic distortion ratio are detected, a set of fuzzy rules are formulated for fuzzy reasoning, the electric leakage fault detection result is determined, and the accuracy of electric leakage fault detection is improved.

The invention provides a temperature drift compensation method, device and equipment for a Hall current sensor, and relates to the technical field of Hall sensors. The method is applied to a temperature excursion compensation system, the temperature excursion compensation system comprises a temperature sensor, a microprocessor, a temperature excursion prediction model, a compensation signal generation module and a differential amplification circuit, and the temperature excursion compensation method comprises the following steps: acquiring environment temperature data of a Hall current sensor by using the temperature sensor; the microprocessor calculates a temperature drift error parameter corresponding to the current environment temperature data based on the environment temperature data and a temperature drift prediction model; the compensation signal generation module generates a corresponding compensation signal based on the temperature drift error parameter, and the compensation signal and the temperature drift error represented by the temperature drift error parameter are equal in size and opposite in direction; and superposing the compensation signal and an original sampling signal of the Hall current sensor through a differential amplification circuit to obtain a final current signal. The measurement accuracy of the Hall current sensor can be improved.

The invention relates to the technical field of unmanned aerial vehicles, provides an unmanned aerial vehicle fusion height estimation method, an unmanned aerial vehicle and a medium, and aims to solve the problem that a stable and credible height estimation value cannot be provided due to IMU measurement errors when both RTK and a barometer fail. The method comprises the following steps: performing high-frequency noise filtering on the original acceleration of the inertial measurement unit to obtain a first acceleration value; performing first-order difference on the speed of the global positioning system to obtain an acceleration compensation value; constructing a state space model containing a vertical speed, an acceleration and an accelerometer zero offset drift error; the first acceleration and the acceleration compensation value are fused through Kalman filtering, and drifting is estimated and stripped in real time; and outputting the smooth height by using trapezoidal integral. The device can output a whole-course continuous height estimation value with the drift distance smaller than 0.3 m / min and the bandwidth larger than or equal to 2 Hz, and is suitable for stable flight and uninterrupted operation when both the RTK and the barometer fail in complex scenes such as agricultural plant protection.

The invention relates to an aiming point dynamic stabilization and automatic calibration method fusing inertial measurement unit data, and belongs to the technical field of aiming equipment dynamic control. The method comprises the following steps: acquiring attitude data of an inertial measurement unit, and constructing a multi-source data matrix in combination with real-time position data of an aiming point and environmental interference data; after time sequence synchronization and drift suppression are carried out on multi-source data, associated feature vectors are extracted through multi-modal feature fusion; inputting a self-adaptive extended state observer to estimate total disturbance and generate an anti-interference compensation amount, constructing a kinetic model in combination with a nonlinear model prediction controller, solving a multi-objective optimization problem, and generating an attitude compensation control sequence to realize dynamic stability of an aiming point; and finally, aiming deviation is calculated in real time to trigger double-closed-loop calibration, an inner ring corrects the drift error of the inertial measurement unit, and an outer ring optimizes parameters of the observer and the controller. According to the invention, environmental interference and inertial drift are effectively suppressed, the dynamic aiming stability is improved, and the long-term aiming reliability is guaranteed through closed-loop calibration.

The invention relates to the technical field of temperature measurement, and discloses a mining distributed optical fiber temperature measurement method, system and device, and the method comprises the steps: synchronously injecting a temperature measurement pulse and a reference pulse, and collecting an optical fiber backscattering signal; strain-free temperature data are obtained through anti-strain demodulation and discrete temperature integration; performing strain compensation according to the real-time difference value to generate strain compensation temperature data; meanwhile, on the basis of optical fiber space distribution, weighting processing is conducted on the reference pulse temperature drift feature space to obtain compensation quantity; and the compensation amount and strain compensation data are fused, a mining global heat supply network is constructed through a temperature field reconstruction algorithm, and an anti-drift temperature field is output. A double-path anti-drift mechanism is realized through double pulse pairs, mechanical interference is eliminated in combination with anti-strain demodulation, and a temperature drift error is corrected in real time by utilizing space weighting and dynamic fusion, so that high-precision and high-stability distributed temperature monitoring is realized in a complex mine environment, and the problems of drift accumulation and precision attenuation in long-distance optical fiber temperature measurement are solved.

The invention belongs to the field of aerospace sensors, and discloses an intelligent wide-range pressure measurement system and method for an aero-engine. The system comprises a pressure acquisition module which comprises at least two pressure sensors with different measuring ranges and overlapped measuring intervals, and an electromagnetic valve group used for switching gas circuits of the pressure sensors; the intelligent control module communicates with an engine FADEC to obtain real-time working condition parameters, predicts the pressure change trend in combination with a pre-stored pneumatic model, switches gas circuits in advance before the pressure reaches a range critical point, triggers a special collection mode to lock an adaptive sensor under a transient working condition, and collects data at the highest sampling rate. The measurement method comprises the steps of working condition parameter acquisition, pressure trend prediction, advanced range switching and self-diagnosis calibration, and through multi-sensor data comparison under environment pressure or stable working conditions, temperature drift errors are dynamically compensated, and faults of the sensors and transmission pipelines are accurately diagnosed. According to the scheme, the problems of switching delay, data distortion, sensor precision drift and difficulty in fault discovery of a traditional system are effectively solved, high precision and stability of full-range pressure measurement are guaranteed, and reliable support is provided for precise regulation and control and flight safety of an aero-engine.

The application relates to the technical field of drainage control, in particular to a liquid level sensing drainage control method and system based on cooperation of an electronic device and a float ball, which comprises the following steps: fusing float ball angular displacement, capacitance value and acceleration disturbance data to construct a liquid level state observer; introducing a dynamic compensation factor to strip liquid sloshing interference and obtain an accurate liquid level reference value; constructing a composite control vector based on liquid level deviation and change rate to analyze and generate a drainage instruction to control a valve action; and simultaneously establishing an adaptive feedback adjustment mechanism to dynamically calibrate observer parameters by using liquid level response residual error and offset actuator drift error; and the technical scheme can significantly improve the robustness of drainage control.

The invention provides a drift error self-calibration method, circuit and system based on a capacitance water level detection system, and the method comprises the steps: obtaining a current count value of a reference pole piece, the current count value being used for representing a system drift amount irrelevant to a liquid level; acquiring a preset calibration reference value, comparing the calibration reference value with the current count value to obtain a comparison result, and determining whether the comparison result is in a preset normal interval; and when the comparison result is in the preset normal interval, determining a calibration factor according to the comparison result, and correcting the original count value of the detected pole piece by using the calibration factor to obtain a corrected detection value. Real-time self-calibration of the drift error is achieved in the operation process, and the precision and stability of water level detection are improved.

The invention provides an autonomous navigation method based on a BIM-SLAM technology, relates to the field of autonomous navigation and environmental perception, and solves the problems of positioning drift, misjudgment of closed-loop detection and poor dynamic environmental adaptability of a traditional SLAM system in a complex building environment. The method comprises the steps of performing path simulation based on a BIM model to obtain initial session data in a simulation environment; in the actual environment of the target area, when the robot carries out environment scanning and path execution through the SLAM system, actual session data is correspondingly generated; aligning a preset number of actual session data with the initial session data, performing closed-loop detection, and correcting the drift error of the map; based on the difference between the actual session data and the initial session data, newly added or removed objects in the actual environment of the target area are detected, and the map is updated and output to serve as the autonomous navigation type movement basis of the robot. According to the invention, the navigation precision and robustness of the robot in a complex environment are effectively improved.

The application provides a spacecraft autonomous navigation method and electronic equipment. The spacecraft autonomous navigation method comprises the following steps: determining technical indexes of an optical sensor according to navigation requirements, and determining a configuration of the optical sensor according to orbit information of the spacecraft; collecting a star map by using the optical sensor with the determined technical indexes and configuration, processing the star map, identifying a refraction star and extracting a refraction angle; and using a Kalman filtering algorithm to perform information fusion on information output by an inertial navigation system and a refraction apparent height calculated based on the refraction angle, so as to correct navigation errors and obtain corrected navigation information. The application corrects drift errors of the inertial navigation by astronomical navigation, maintains continuous navigation information by using the inertial navigation when the astronomical system is unavailable, and achieves the purpose of improving navigation accuracy.

An embodiment of the present application provides a time-of-flight ranging module and a temperature drift compensation method therefor. The module includes: a driving circuit and a mirror circuit. The mirror circuit receives the same voltage signal as the driving circuit, and the frequency change of the output signal of the mirror circuit characterizes the delay change of the output signal of the driving circuit relative to the input signal. The mirror circuit generates output signals with a first frequency and a second frequency at a calibration temperature and a current temperature respectively; the driving circuit amplifies the driving signal at the current temperature to obtain the temperature drift depth data of the current temperature relative to the calibration temperature; so that the processing circuit obtains the delay difference of the driving circuit from the calibration temperature to the current temperature according to the first frequency and the second frequency, obtains the temperature drift error of the driving circuit from the calibration temperature to the current temperature according to the delay difference and the temperature drift compensation coefficient of the driving circuit, and performs temperature drift compensation on the temperature drift depth data at the current temperature according to the temperature drift error.