9 results about "GPS/INS" patented technology

The invention discloses a cascade learning type multi-source fusion positioning method and system under satellite denial. The method comprises the following steps: firstly, constructing a system sensor mathematical model which comprises an INS error model, a WSS / INS integrated navigation model and a GPS / INS integrated navigation model; then designing a neural network model based on a cascade learning CL algorithm; when the satellite is available, training a neural network model based on a cascade learning CL algorithm; when the satellite is denied, the neural network model which is completely trained and is based on the cascade learning CL algorithm is utilized to predict the pseudo GPS position, and the GPS blank is filled up. The system comprises a sensor mathematical model building module, a CL algorithm model building module, a training module and a positioning prediction module. The method improves the positioning precision of the vehicle in the GPS failure period, is excellent in performance especially in a complex environment and under long-time interruption, reduces the positioning error, improves the overall performance, and has important application value for vehicle positioning in the technical fields of intelligent transportation and automatic driving.

The invention provides an unmanned aerial vehicle control-oriented TCN-LSTM series network multi-source state real-time sensing method and system. The method comprises the following steps of: constructing a deep neural network model formed by connecting a TCN and an LSTM in series; the speed, attitude and position information of the unmanned aerial vehicle is acquired through cooperation of the RTK-GPS, the INS and the IMU, and time alignment is carried out on IMU data and RTK-GPS / INS data by using an interpolation method; the collected data is divided into a training set, a verification set and a test set, and a composite loss function fusing RMSE, MAE, quaternion angle errors and offset errors is adopted to train and evaluate the model; serializing sensor data based on a sliding time window strategy to form an input feature vector, and standardizing IMU data according to channels; and inputting the standardized sensor data into the TCN-LSTM model, and outputting a state estimation result for navigation, path planning or closed-loop control.

The invention provides an integrated navigation information fusion method and system considering driving state deviation, and belongs to the technical field of positioning navigation, Kalman gains generated by a first filter in past n periods are obtained, a position difference and a speed difference between an INS and a GPS in a current GPS signal interruption period are predicted by using a pre-trained LSTM, and the position difference and the speed difference between the INS and the GPS in the current GPS signal interruption period are calculated. The vehicle driving state deviation is obtained; using a second filter to update a filter gain with the predicted vehicle driving state deviation as an input; and predicting the difference between the output of the first filter and the output of the second filter by using a pre-trained TL-LSTM, and correcting the INS navigation result by taking the additionally corrected optimal estimated value as final compensation. The GPS / INS integrated navigation information fusion considering the driving state deviation combines a long short-term memory network (LSTM) and error state Kalman filtering (ESKF), and secondary correction is performed on an INS navigation result to ensure the positioning precision of the integrated navigation system in a lock losing state.

Systems and methods may include tracking one or a plurality features across a decreasing scale of tiled sets of one or more images. Aspects may include generating point data for each of the tracked features based on a coordinate system relative to the first camera or the second camera, and transforming the point data to a Global Positioning System / Inertial Navigation System (GPS / INS) coordinate system based on (1) an origin of a first GPS device coupled to the first camera and (2) a rotation of the first camera relative to an INS device coupled to the first camera. Aspects may include generating, based on the transformed point data, a geodetic mapping function, determining, based on the geodetic mapping function, georegistered coordinates of the tracked features, using the georegistered coordinates of the tracked features to characterize the water flow.

The present invention discloses a control method, device and storage medium for a manta ray - like bionic fish based on reinforcement learning. The bionic fish control method controls the manta ray - like bionic fish through a reinforcement learning algorithm to achieve the task of the bionic fish autonomously swimming to a target point. The current motion state of the bionic fish is observed as the input of the reinforcement learning algorithm, and the output direction and speed coefficient are used to control the swimming direction and speed of the bionic fish. Compared with the method of controlling the joint motion angle, the present invention improves the training efficiency, control efficiency and robustness. In addition, the present invention uses GPS / INS as a positioning and navigation system, which is more practical than the positioning method by photographing the pose of the bionic fish.

The invention discloses a multi-mode airborne aviation communication navigation monitoring comprehensive simulation system and method, and the system takes a main control module as a core processing center, and is responsible for data collection, instruction distribution, and parameter configuration and storage. The system integrates a VHF / UHF communication module, a DME navigation module, a monitoring module and a GPS / INS navigation module. Wherein the VHF / UHF communication module, the DME navigation module and the monitoring module all adopt a unified highly integrated hardware architecture, the core of the VHF / UHF communication module, the DME navigation module and the monitoring module is a signal processor integrated with an FPGA and a DSP and a chip with analog-to-digital / digital-to-analog conversion and radio frequency transceiving functions, and the VHF / UHF communication module, the DME navigation module and the monitoring module are respectively connected with a UV antenna, a DME antenna and a monitoring antenna; and the GPS / INS navigation module is connected with the GPS antenna. The system integrates communication, navigation and monitoring functions through a highly integrated unified hardware architecture, solves the problems that traditional equipment is discrete and poor in collaboration, and improves the test efficiency and reliability.

The invention relates to the Vertical Gliding Guided Tactical Munition or in other words, the Tactical Combat Unit Propeller System (TAMU-P), which is a guided miniature munitions system that can be dropped from cargo and fighter planes, helicopters, Unmanned Aerial Vehicles (UAVs), portable small UAV (Drones) type vehicles or launcher land platforms such as mortars, can aim at the target position by means of the propellers placed at 120-degree intervals and perpendicular to the ammunition body with the help of GPS / INS or Laser seeker by getting to a vertical position by creating a parachute effect when the flaps on the rear of the ammunition open shortly after being launched and can even engage the target by tracking it at very low speeds.

The invention discloses a low-cost intelligent terminal satellite and inertial integrated precise point positioning method and device, and belongs to the technical field of navigation positioning. The method comprises the following steps: aiming at the problem that the pseudo-range inter-frequency deviation of the low-cost terminal is large and gradually varied, carrying out deviation estimation and correction by adopting a semi-parameter estimation and compensation least square method; for observation value abnormity and deletion, RAIM and LSTM are fused to construct an early warning-recovery-verification closed loop mechanism; aiming at a dual-frequency and single-frequency observation value coexistence scene, a mixed ionosphere delay processing strategy is adopted, and differential correction is realized through ionosphere elimination combination and GIM constraint; aiming at the problem of combination switching lag, constructing a fuzzy-neural network adaptive decision model, and dynamically selecting a GNSS / INS combination mode based on multi-dimensional features; and position parameter estimation and post-processing are realized through an integrated algorithm framework. According to the invention, high-precision and high-robustness precise point positioning is realized under the condition of low-cost hardware.

The invention belongs to the technical field of road traffic safety, and discloses an autonomous road traffic system vehicle rollover risk early warning method and system, and the method comprises the steps: collecting the kinetic parameters, road parameters and environmental parameters of an autonomous vehicle; based on GPS / INS positioning data, in combination with a roadside unit collaborative awareness technology, space-time synchronization and dynamic mapping of a vehicle planning track and road environment parameters are carried out, and a space-time coupling sequence used for rollover prediction is constructed; calculating a real-time rollover risk index according to the four-wheel load obtained by the data of the vehicle detector; according to the real-time rollover risk index, taking the kinetic parameters, the road parameters and the environmental parameters of the current vehicle as input, and adopting an extreme random tree algorithm to predict a rollover risk index value in a future preset time; and judging a rollover risk level according to the predicted rollover risk index value, and outputting early warning information for an autonomous road traffic system to perform safety control and path adjustment.