51 results about "Mems imu" patented technology

A GPS / IMU safety sensor platform is proposed, consisting of data fusion Processors, GNSS Signal Acquisition and Tracking Processors, MEMS IMU sensors, one or multiple accelerometers able to provide orientation information, optional V2V communication modules, and optional V2I communication modules. The data fusion processors provide interface ports to GNSS / IMU processors, odometers, video (Visual / Infrared) cameras installed in the vehicle, V2V relative positioning sensors (laser, radar or any other distance measuring), and V2V and V2I communication modules. The data fusion processors are interfaced to a driver warning system and optionally to the vehicle controls for providing safety warning messages to drivers, or for automatic control the vehicle for preventing and reducing accidents.

The invention discloses a microminiature personal combined navigation system as well as a navigating and positioning method thereof. The system is composed of a subsystem installed on the foot part of a human body and a subsystem installed on the trunk position, wherein the subsystem installed on the foot part comprises an MEMS IMU (Micro-electromechanical Systems Inertial Measurement Unit), a magnetometer and a communication module; and the subsystem installed on the trunk position comprises a satellite navigation receiver, a Doppler velometer, an atmospheric pressure altimeter, a communication module and a microminiature navigation computer. The positioning method comprises the following steps of: collecting the MEMS IMU signal; modeling and correcting the random error of a gyroscope and an accelerometer; initially aligning an MEMS inertial navigation system; resolving strapdown inertial navigation, and correcting zero speed; carrying out combined navigation of the MEMS inertial navigation system / satellite navigation receiver / the Doppler velometer / the magnetometer / and the atmospheric pressure altimeter; and displaying the navigation result in real time. The microminiature individual combined navigation system is convenient to individually carry, individual real-time gesture fixing, velocity measurement and positioning can be realized, and whole and precise real-time navigation positioning information can be provided for pedestrians, operating personnel, soldiers, rescue workers and the like in the complex electromagnetic environment.

The invention provides a combined locating and orienting device with lower cost and a combined locating and orienting method thereof. The device mainly includes an MEMS INS consisting of an MEMS IMU and a navigation computer, a GPS receiver, a 3D digital electric compass, an altometer, an aerodromometer, a power module, a box body, a socket connector, etc; wherein, the MEMS INS includes 9 MEMS gyroscopes and 6 double-axis MEMS accelerometers which respectively measure the palstance and the acceleration of a moving carrier; then the palstance and the acceleration are inputted into a navigation calculating program to calculate the information like the pose, the position and the speed of an obtained carrier. Simultaneously, the navigation computer regularly collects the information of the navigation sub-units like the GPS receiver, the 3D digital electric compass, the aerodromometer and the altometer by a 232 series port and obtains the best navigation information like the position, the pose, the speed and the height of the carrier by information fusion processing; the precision of the invention is better than a single sub-system in the device. The combined locating and orienting device with lower cost has the advantages of small size, low power consumption, low cost, complete functions and abundant interfaces, thus being capable of completely meeting the locating and orienting requirements with middle precision for carrying the carrier on the ground or in the air.

An object positioning solves said problems encountered in machine vision, which employs electro-optic (EO) image sensors enhanced with integrated laser ranger, global positioning system / inertial measurement unit, and integrates these data to get reliable and real time object position. An object positioning and data integrating system comprises EO sensors, a MEMS IMU, a GPS receiver, a laser ranger, a preprocessing module, a segmentation module, a detection module, a recognition module, a 3D positioning module, and a tracking module, in which autonomous, reliable and real time object positioning and tracking can be achieved.

This invention documents the efforts on the research and development of a miniaturized GPS / MEMS IMU integrated navigation system. A miniaturized GPS / MEMS IMU integrated navigation system is presented; Laser Dynamic Range Imager (LDRI) based alignment algorithm for space applications is discussed. Two navigation cameras are also included to measure the range and range rate which can be integrated into the GPS / MEMS IMU system to enhance the navigation solution.

The invention discloses a pedestrian autonomous navigation calculation algorithm based on an MEMS-IMU. Two IMU systems are simultaneously and fixedly connected with the two feet of the user of a pedestrian navigation system; the two systems respectively perform a strapdown inertial navigation calculation algorithm and a zero-speed correcting algorithm on the basis of Kalman filtering, and then the positioning information of the two feet is fused; when the calculation distance between two feet exceeds the largest step size gamma between the two feet, inequality constraint is performed on navigation results of two IMUs by adopting a state constraint Kalman filtering algorithm, so that vague human physiological property problem is converted into a rigid mathematical problem, the optimal estimation of navigation results is achieved, and pedestrian navigational positioning function with higher accuracy is achieved.

An object positioning solves said problems encountered in machine vision, which employs electro-optic (EO) image sensors enhanced with integrated laser ranger, global positioning system / inertial measurement unit, and integrates these data to get reliable and real time object position. An object positioning and data integrating system comprises EO sensors, a MEMS IMU, a GPS receiver, a laser ranger, a preprocessing module, a segmentation module, a detection module, a recognition module, a 3D positioning module, and a tracking module, in which autonomous, reliable and real time object positioning and tracking can be achieved.

The invention provides a BD, GPS and MEMS based integrated navigation system and method on account of defects f prior navigation systems. The system comprises an MEMS-IMU module, a GNSS module, a magnetometer module and an integrated navigation computer. The MEMS-IMU module, THE GNSS module and the magnetometer module are connected with the integrated navigation system respectively. By the aid of the navigation method, corrected position values, speed values and corrected attitude angle values can be output. The system and the method have the advantages of being anti-overloading, miniaturized, low in power consumption and cost, provided with high impact resistance and particularly applicable to various war environments. By the aid of the navigation method, drifting of gyroscopes, accelerometer and magnetometers can be suppressed, and the stability and the accuracy of the system are improved.

This invention documents the efforts on the research and development of a miniaturized GPS / MEMS IMU integrated navigation system. A miniaturized GPS / MEMS IMU integrated navigation system is presented; Laser Dynamic Range Imager (LDRI) based alignment algorithm for space applications is discussed. Two navigation cameras are also included to measure the range and range rate which can be integrated into the GPS / MEMS IMU system to enhance the navigation solution.

The invention relates to the technical field of navigation and positioning, and particularly relates to an MEMS-based GNSS / IMU vehicle-mounted real-time integrated navigation and positioning method. The process comprises the steps that dynamic initial alignment is performed by using the output information of the current moment and the previous adjacent moment of the IMU and the output informationof the current moment of the GNSS; strapdown solving is performed by using the IMU information of the two successive moments, and the covariance matrix of the moment is obtained through Kalman prediction; the time condition is met and the fusion solving is triggered, the GNSS delay deviation dt is solved by using the corresponding UTC time of the IMU and the GNSS of the current moment, and the information of the GNSS at the current IMU moment is reckoned; and Kalman filtering updating is performed, the state error quantity is fed back to correct the navigation information and cyclic solving isperformed. The low-cost MEMS IMU is used and the GNSS delay output error is eliminated so that the positioning accuracy can be enhanced and the real-time vehicle-mounted integrated navigation and positioning method can be realized.

The invention provides an MEMS-IMU (Micro-electromechanical Systems-Inertial Measurement Unit) total-temperature and total-parameter calibration and compensation method. Temperature-control rotary table calibration and precise centrifugal calibration are tightly combined to complement each other and have a complementary action; the temperature-control rotary table calibration is used for calibrating a zero offset, a temperature coefficient, a scale coefficient, an installation coupling error and a non-linear error of a gyroscope in an MEMS-IMU, and zero offset and a temperature coefficient ofan accelerometer; the precise centrifugal calibration can be used for calibrating an acceleration effect coefficient of the gyroscope, and a scale factor, an installation coupling error, non-linear error, a lever arm effect and the like of the accelerometer; total-error parameters of the MEMS-IMU under a total-temperature state can be accurately calibrated, so that the precision of the MEMS-IMU inan actual application process is improved.

The invention discloses an initial alignment method for an MEMS-IMU. Through the initial alignment method, the initial rough alignment time of a strapdown inertial system is further shortened, and the precision of the strapdown inertial system is further improved. The initial alignment method comprises the following steps that 1, sensor data are acquired, wherein the sensor data comprise the data of an MEMS gyroscope and an MEMS accelerometer; 2, initial alignment coordinate systems are established, wherein the initial alignment coordinate systems comprise the solidified carrier coordinate system, the earth coordinate system, the navigation coordinate system and the carrier coordinate system; 3, initial alignment objective functions are established, and an optimal speed reducing method of quick alignment is constructed; 4, a parameter equation of the optimal speed reducing method is determined through the complementary filter principle; 5, a carrier attitude angle is resolved through an quaternion updating algorithm, and calculation of an initial attitude matrix is achieved. According to the initial alignment method for the MEMS-IMU, the calculation precision and efficiency of an initial alignment algorithm are effectively improved, and the application range is wide.

The invention provides a seamless autonomous navigation algorithm for a small UAV based on a topocentric coordinate system. The algorithm uses the topocentric coordinate system as a navigation coordinate system, uses multi-sensor redundancy to assist strapdown inertial navigation based on the low-cost MEMS IMU, and uses the extended Kalman filter to complete data fusion so as to solve the location, the speed and the attitude of the UAV. The navigation algorithm uses a sensor data health state management system to adaptively switch the multi-sensor data participating in the navigation data fusion, solidifies a state equation dimension and a range equation dimension, simplifies the data fusion algorithm and ensures the seamless autonomous navigation of the UAV in the presence or absence of GNSS.

The invention discloses an underground pipeline trajectory detection system based on inertia measurement. The system is composed of two sub systems. A data acquisition system is loaded in a mechanicalbody to form a pipeline surveying instrument which comprises an MEMS-IMU, a speedometer, a built-in lithium battery and a data acquisition plate. The MEMS-IMU is used for providing a real-time gesture information of the surveying instrument, the speedometer is used for providing real-time journey information of the surveying instrument, the data acquisition plate receives sensor data and stores the data in an SD card, and after measurement, the stored data is uploaded to an upper computer through a USB interface. An upper computer data processing system obtains a real-time gesture angle through inertial navigation calculation and information infusion, carries out dead reckoning by combining the journey information to obtain a walking trajectory of the surveying instrument in the pipeline,and corrects the trajectory by means of the inlet / outlet position of the pipeline to obtain a tested pipeline trajectory. The measuring method is of autonomy, is not affected by external environmentand buried depth of pipelines, and by using non-excavation means, the system does not need ground operations, so that the system is economic, efficient and environment-friendly.

The invention provides an underwater carrier integrated navigation system based on MEMS IMU / magnetometer / DVL integration, which comprises an initial alignment process, an inertia calculation process,a speed measurement Kalman filter and a course measurement Kalman filter; wherein the initial alignment process uses a magnetometer and an accelerometer to complete initial course attitude calculation; in the inertial calculation process, recursive calculation of carrier poses is carried out by utilizing data of an MEMS IMU, speed difference output by the MEMS IMU and a DVL serves as a filter forprimary measurement in speed measurement Kalman filtering, navigation parameters such as heading and poses are estimated by utilizing filtering, and measurement precision such as horizontal poses is improved through feedback correction; secondly, magnetic heading information is calculated in combination with the obtained horizontal attitude information and the magnetometer measurement value, heading measurement Kalman filtering takes the difference between the heading obtained through primary feedback correction and the magnetic heading as a filter for secondary measurement, then filtering isperformed, and high-precision navigation parameters such as heading, attitude and speed are obtained; and therefore, the positioning precision of the system is greatly improved.

Embodiments of the invention provide a method and device for compensating temperature drift errors, and an integrated navigation system. The method comprises the following steps: acquiring the sampleoperating temperatures of a microelectromechanical system inertial measurement unit (MEMS IMU); acquiring the error parameter values of the measurement results of the MEMS IMU corresponding to the sample operating temperatures; carrying out fitting based on a plurality of the sample operating temperatures and a plurality of the error parameter values so as to obtain an error parameter-temperaturerelation curve; and compensating for the temperature drift errors of the MEMS IMU according to the curve. The method for compensating the temperature drift errors in the embodiments of the invention compensates for the temperature drift errors of the MEMS IMU on line by using the error parameter-temperature relation curve obtained after fitting of a great amount of MEMS IMU sample data generated in actual navigation process. The curve is updated based on real-time navigation information, so navigation accuracy is improved, cost is reduced, and implementation of the method is facilitated.

The invention discloses an IMU data denoising method based on a recurrent neural network, and the method comprises the steps: building an IMU data time sequence sample data set, building the recurrentneural network, and carrying out the training optimization to obtain a weight file; and finally obtaining a deployment model. According to the method, a time sequence prediction method is introducedinto measurement data of a micro-electromechanical system inertial measurement unit (MEMS IMU), the measurement data is regarded as a time sequence, a long-short-term memory network (LSTM) is designedto extract a nonlinear relation of the time sequence, and the effect of removing noise is achieved through a sequence prediction method. Compared with a traditional denoising method based on a statistical model, the algorithm has better robustness and generalization ability, and the randomness of original data is not changed. The method has important application value in the aspects of inertial technology, integrated navigation and the like.

The invention discloses a bus driver driving level assessment method based on an MEMS IMU. According to the method, a three-axis MEMS gyroscope, a three-axis MEMS accelerometer, a three-axis geomagnetic sensor, a GPS and a temperature sensor respectively collect data to obtain state information of a bus, and the state information is sent to a DSP processor; the DSP processor judges whether each piece of the received state information of the bus exceeds a corresponding threshold value or not, and the information exceeding the threshold value is recorded as improper operation data; the change rate of acceleration is calculated according to the received state information of the bus, and the change rate information of the acceleration is added into the state information of the bus; the state information of the bus and the improper operation data are stored in a data storage SD card. After bus driving is finished, a computer reads the information stored in the data storage SD card and assesses the driving level of a bus driver. Travelling data of the bus are collected in real time, an alarm is given in real time, and therefore travelling safety of the bus is improved.

The invention relates to a MEMS-IMU-based method and device for identifying a pedestrian movement pattern. An acceleration in the x-axis direction and an angular velocity in the y-axis direction in anMEMS-IMU are at least collected; difference processing is performed on the collected acceleration in the x-axis direction and an initial acceleration value, an extreme value greater than zero is setas an acceleration peak value, and an extreme value less than zero is set as an acceleration valley value; difference processing is performed on the collected angular velocity in the y-axis directionand an initial angular velocity, an extreme value greater than zero is set as an angular velocity peak value and an extreme value less than zero is set as an angular velocity valley value; the movement state of a pedestrian is determined; if the acceleration valley value occurs first in the acceleration in the x-axis direction in the period starting with releasing of the stationary state of the pedestrian, the state of the pedestrian is determined to be a state of going upstairs; and if the angular velocity valley value occurs first in the angular velocity in the y-axis direction, the state ofthe pedestrian is determined to be a state of going downstairs. Therefore, with the method for detecting the motion pattern states of people moving in the building, the movement states of people areidentified.

The invention provides a gait space-time parameter calculation method based on a portable gait analysis system. The gait space-time parameter calculation method comprises the steps of time parameter calculation and space parameter calculation. The method integrates the two types of parameter calculation and a detection method to make their respective advantages complementary to each other and hasthe advantages of eliminating MEMS IMU sensor data, obtaining speed and position information including errors accumulated over time through integration and operation, improving the accuracy of gait parameter calculation, and meanwhile solving the problem that a plantar pressure analysis method cannot calculate gait space parameter such as stride, walking distance and walking speed.

The invention discloses a MEMS-IMU-based heading feedback and correction method for indoor pedestrian navigation, belonging to the field of pedestrian navigation. According to the method, it is defined that straight heading along a principal direction of a pedestrian is defined as a heading feedback condition on the basis of typical building structures, a heading difference is constructed as a quantity of state, and adaptive unscented Kalman filtering (AUKF) is carried out; the sum of an optimal estimated result and a strapdown heading angle is used as a feedback heading angle; and a feedbackheading value is allowed to participate into quaternion resolution, so accumulation of heading errors is reduced. Compared with no feedback, time for exact solution of the heading angle is improved bytwo times or more due to usage of feedback, so the method has good practicality to improvement of navigation precision.

The invention discloses a low-cost odometer design method based on an MEMS IMU, and the method comprises the following steps: 1, enabling the IMU to be installed on the side surface of a wheel, enabling the IMU to rotate along with the wheel, and measuring the non-gravitational acceleration and angular velocity of the wheel relative to an inertial system; 2, establishing an output model of the IMUfor the IMU mounted on the wheel while considering the motion constraint of the vehicle; 3, establishing a Kalman filtering system model based on a constraint relation between states by taking a wheel rotation angle, an angular velocity and an angular acceleration as state variables, and establishing an observation model based on an IMU output model; 4, calculating the speed and mileage based onthe artificial neural network and updating the parameters, the method has the advantages of low cost, accurate result and the like, the defects of a traditional odometer are overcome, and the method has great application potential.

The present disclosure relates to a gyro-based surveying tool for surveying of holes oriented in a basically vertical direction in areas with no line-of-sight connection to the sky. The gyro-based surveying tool comprises a surveying head and an analysing unit. The surveying head comprises a plurality of MicroElectroMechanical-systems-inertial-measurement-unit arrangements, MEMS-IMU arrangements. Each of the MEMS-IMU arrangements is arranged to transmit information relating to their measurement results to the analysing unit. The analysing unit is arranged to receive and analyse said transmitted information relating to the measurement results from the plurality of MEMS-IMU arrangements so as to calculate a combined measurement result. The surveying tool further comprises means for calculating an attitude and / or position of said surveying head based on said combined measurement result.The present disclosure also relates to a surveying method, a computer program for surveying, and a computer program product.

The invention discloses a compound MEMS-IMU electronic image stabilizing apparatus. The electronic image stabilizing apparatus has a simple structure, low cost, high image stabilizing precision, high anti-interference performance, and small operation amount of image processing motion estimation. The apparatus is integrated by an image sensor reading circuit (3), a signal processor (4), an MEMS-IMU (5) and a circuit component (6). An image sensor (2) converts an optical signal from an optical lens (1) into an electrical signal, and transmits the electrical signal to the reading circuit so as to output original video image data; and the signal processor inputs inertia measurement information of the MEMS-IMU in signal processing of image electronic image stabilization, so as to merge the original video image data with inertia measurement data output by the MEMS-IMU, the motion vector of a camera is solved through MEMS-IMU information, jitter component is separated through adaptive Kalman filter, and motion compensation is performed on the original video data so as to output stable video data.

The invention discloses a vehicle-mounted autonomous navigation method based on carrier motion condition constraint and uniaxial rotation modulation, whichbelongs to the technical field of navigation.According to the method, anMEMS IMU is mounted in the center of a wheel, so that the MEMS IMU rotates along with the running of a vehicle. The forward speed of the carrier is calculated based on theoutput of the rotary IMU, and a three-dimensional speed observed quantity of the carrier is formed in combination with a non-integrity constraint condition (NHC); an improved strapdown inertial navigation calculation equation is utilized to calculate carrier position, speed and attitude information based on inertial output of a rotary IMU. On the basis of extended Kalman filtering, the three-dimensional speed of a carrier is taken as an observed quantity, online estimation of an inertial system error is realized, and errors of the position, speed and attitude of the carrier are corrected, so that the vehicle-mounted autonomous navigation precision is improved.

The invention provides a combined locating and orienting device with lower cost and a combined locating and orienting method thereof. The device mainly includes an MEMS INS consisting of an MEMS IMU and a navigation computer, a GPS receiver, a 3D digital electric compass, an altometer, an aerodromometer, a power module, a box body, a socket connector, etc; wherein, the MEMS INS includes 9 MEMS gyroscopes and 6 double-axis MEMS accelerometers which respectively measure the palstance and the acceleration of a moving carrier; then the palstance and the acceleration are inputted into a navigationcalculating program to calculate the information like the pose, the position and the speed of an obtained carrier. Simultaneously, the navigation computer regularly collects the information of the navigation sub-units like the GPS receiver, the 3D digital electric compass, the aerodromometer and the altometer by a 232 series port and obtains the best navigation information like the position, the pose, the speed and the height of the carrier by information fusion processing; the precision of the invention is better than a single sub-system in the device. The combined locating and orienting device with lower cost has the advantages of small size, low power consumption, low cost, complete functions and abundant interfaces, thus being capable of completely meeting the locating and orienting requirements with middle precision for carrying the carrier on the ground or in the air.

The invention provides a method for positioning vertical direction of object by utilizing an inertial navigation system. The technical problem can be solved that an existing object height measuring technology is easily affected by the environment and accordingly measurement cannot be achieved or measurement errors are larger. The method comprises the following steps: S100, utilizing existing vehicle-mounted MEMS IMU hardware to import a CAN signal into a navigation device; S200, in the transmission DBC format of an IMU arranged for the navigation device, resolving the measurement data of the IMU at the device side, according to the real-time measured acceleration data in the CAN signal, calculating the acceleration in the vertical direction and integrating the vertical acceleration to obtain a real-time height value; S300, enabling a navigation function, and judging the obtained real-time height value. The method utilizes a vehicle or an instrument equipped with an inertial navigationsystem to acquire the change of an object at the height, accordingly obtains the relative height of the object, is not affected by the environment and is high in measurement precision.

The invention discloses an all-attitude solution method for a micro-electro-mechanical systemInertial measurement unit (MEMS IMU) under a rocking substrate. The method comprises defining a coordinatesystem that satisfies a preset rule, rotating the MEMS IMU in a positive and negative continuous rotation manner in the defined coordinate system, acquiring data of an MEMS inertial device in rotation, and according to the data of the MEMS inertial device, through the combination of the inertial alignment algorithm and the Mahony algorithm, acquiring the all-attitude solution result of the MEMS IMU. The method is free of auxiliary information of a satellite or a magnetometer, can achieve a certain all-attitude calculation accuracy and can effectively improve the accuracy of the calculation, which has an important application value in the absence of a satellite signal or a magnetic field interference environment. The MEMS IMU has the advantages of low cost, small size, impact resistance andthe like, can be widely used and effectively improves the applicability.

The invention discloses an automatic hammering robot system, which is characterized in that the system comprises a UWB tag, a MEMS IMU, a robot body, a hammering command wireless module, a wireless APand an alarm system; a MCU control center and a WIFI module are set inside the robot body, a walking mechanism is arranged at the bottom of the robot body, a navigation module is arranged on the robot body, a manipulator arm is arranged on one side of the robot body, and the end of the manipulator arm is connected with a UWB base station, a binocular camera, an ultrasonic sensor, a capacitance sensor pushing rod electric cylinder, and a hammering pushing rod electric cylinder; a hammering head is connected with the pushing rod end of the hammering pushing rod electric cylinder; a capacitive sensor is arranged at the end of the push rod of the capacitive sensor push rod cylinder; the alarm system, the hammering command wireless module, the WIFI module and the wireless AP constitute a WIFIlocal area network. The automatic hammering robot system can automatically perform precordial region percussion on a patient with cardiac arrest; In addition, the automatic hammering robot system alsohas the characteristics of hammering back and hammering legs and the like on the human body.