Beihang University

Yanbo Zhu

Zhipeng Wang

Kun Fang

Jingtian Du

Kaiquan Cai

Qiang Li

Yuan Liu

Zhen Gao

Wei Liu

Xin Wang

Hui Wang

Xin Li

Zhibo Zhang

Wei Shao

Kai Kang

Xiaofeng Shi

Quan Zhou

Jingjing Zhao

Hongxia Wang

Xiaopeng Hou

Ludan Song

Jisi Fang

Sikun Wang

Yu Yin

Ziyi Yang

Siqi Huang

Cong Du

Jiatong Chen

Lanchenhui Yu

Zhiqi Shen

Yuanyuan Zhuang

Hongshuo Lyu

Provide is a method for multi-dimensional super-resolution target sensing based on a 5G AeroMACS. The method includes modulating data to be transmitted into a plurality of OFDM symbols using the 5G AeroMACS and transmitting the OFDM symbols, receiving the OFDM symbols in the air via a plurality of receiving antennas, performing data recovery and stacking recovered data into a 3D data tensor, and storing the 3D data tensor into a 3D complex matrix, obtain a multi-dimensional super-resolution spectrogram; obtaining a final target sensing result by using a 3D-CFAR detection algorithm; determining an adjusted operating power level of each of bird-repelling devices in different regions based on the target sensing result; controlling one or more bird-repelling devices in a designated region to operate to repel birds in the designated region; and generating a vehicle regulation instruction and sending the vehicle regulation instruction to a plurality of UAVs to control the plurality of UAVs to drive away from a warning region.

Methods for multi-dimensional super-resolution target sensing based on 5G aeromacs

An ARAIM availability prediction method under a complex terrain environment is provided. The method includes: 1) selecting positioning points according to an air line; 2) calculating terrain shielding angles; 3) predicting visible satellites; 4) determining a fault mode that needs to be monitored; 5) calculating a positioning error variance, an influence coefficient of a nominal deviation, and a variance of a solution separation test statistic; and 6) calculating a threshold of a solution separation test, calculating a protection level, and determining availability. According to the method, the terrain shielding angles are calculated based on terrain model data, and the visible satellites are predicted based on ephemeris data or almanac data to further calculate a protection level, while determining the availability; and the accuracy of availability prediction can, by considering the effect of terrain barriers on the prediction of the visible satellites, be improved to ensure the safety of aircrafts.

ARAIM availability prediction method under complex terrain environment

The present disclosure provides a coordinated multiple access method for multi-cell ground-to-air data transmission, and belongs to the technical field of wireless communication. The method comprises the following steps: S, constructing a model of a coordinated multiple access system for multi-cell ground-to-air data transmission; S, calculating a transmission rate of an aircraft, and constructing a multi-cell airspace and power domain resource allocation optimization problem by taking maximizing a system transmission rate as an optimization objective; S, constructing a Markov decision process model; S, solving the optimization problem using a multi-agent deep reinforcement learning algorithm. The system transmission rate is maximized under the condition that the aircraft can decode the signal correctly and satisfy the constraint of minimum transmission rate, thereby realizing ground-to-air high-speed data transmission. The present disclosure adopts the coordinated multiple access method for multi-cell ground-to-air data transmission, which can realize fast online decision, satisfying the requirements of ground-to-air high-speed data transmission in the high dynamic flight scenario of the aircraft.

Coordinated multiple access method for multi-cell ground-to-air data transmission

The present disclosure relates to a technical field for airborne navigation and discloses a data acquisition system and method for airborne navigation devices based on unmanned aerial vehicle. The system includes an unmanned aerial vehicle flight control system, a navigation devices test antenna array, a multi-channel signal processing module, a signal acquisition module, an ADS-B transmitting module, a GNSS receiver, a UHF data link receiver, a power module and a ground station. The unmanned aerial vehicle is equipped with corresponding modules to receive signals from ground navigation devices, perform corresponding processing and storage, and transmit data to the ground, at the same time, receive control instructions sent by the ground to complete corresponding monitoring, analysis and inspection.

Data acquisition system and method for airborne navigation devices based on unmanned aerial vehicle

The present application provides a 4-dimensional trajectory regulatory decision-making method for air traffic. The method includes: acquiring a node vector set of a target flight to obtain a target node vector set; acquiring the node vector set of all historical flights simultaneously to obtain a historical node vector set; acquiring a similarity between the target node vector set and the node vector set of each historical flight in the historical node vector set to obtain a plurality of similarity data; acquiring a similarity data which is greater than a preset similarity data from plurality of similarity data to obtain a target similarity data; acquiring a historical flight to which the target similarity data belongs to obtain a target historical flight; acquiring a historical decision-making instruction of the target historical flight to obtain a target decision-making instruction.

4-dimensional trajectory regulatory decision-making method for air traffic

Embodiments of the present disclosure provide a method, an apparatus, a device and a storage medium for pre-warning of aircraft flight threat evolution. The method includes: inputting historical threat situation data to an evolution model that has been trained to convergence to output each evolution mode corresponding to the historical threat situation data and a probability corresponding to the evolution mode; obtaining evolution trend data corresponding to the historical threat situation data according to the evolution mode and the probability; assigning a detection task to other aircraft within a preset range of a target aircraft according to a crowdsourcing strategy, and acquiring current actual flight threat information detected by the other aircraft according to the detection task; sending pre-warning information to a pre-warning device if the flight threat meets a pre-warning condition.

Method, apparatus, device and storage medium for pre-warning of aircraft flight threat evolution

The present invention discloses a APNT service positioning and integrity monitoring method and system. The method includes the following steps: determining a positioning accuracy requirement in a target scene; when the positioning accuracy requirement is high-accuracy positioning, determining a position of an aircraft by adopting a combined positioning algorithm, and monitoring the integrity of a combined positioning by adopting a multi-solution separation mode; when the positioning accuracy requirement is low-accuracy positioning, judging whether the aircraft is a high-altitude user; if not, adopting an air-to-air positioning algorithm for a high-altitude user and a low-altitude user based on LDACS to determine the position of the aircraft, and adopting a least square residual method to monitor the integrity of the air-to-air positioning. According to different requirements of users on positioning accuracy and actual application conditions, the present invention can provide a variety of APNT alternative solutions for an aircraft.

APNT service positioning and integrity monitoring method and system

A constellation configuration optimization method of a low earth orbit (LEO) satellite augmentation system for an ARAIM application includes: 1, traversing vertical protection levels after all subset solutions and fault modes under the condition that integrity risk and continuity risk are equally distributed, and determining the constraint conditions of LEO satellite constellation configuration parameters; 2, determining objective functions of LEO satellite constellation configuration parameters x, x, x, x, eliminating calculated values of abnormal vertical protection levels, and screening initial populations of the parameters x, x, x, x; 3, calculating fitness of the objective functions; 4, starting from a second generation population, merging a parent population with an offspring population to form a new offspring population; 5, performing local optimal selection on the new offspring population, screening out a maximum value of the objective functions as an optimal offspring, and repeating step 4 until a genetic algebra is less than a maximum genetic algebra.

Constellation configuration optimization method of LEO satellite augmentation system for ARAIM application

A GBAS integrity risk allocation system based on key satellites is used to perform a GBAS integrity risk allocation method, including: reading data from an ephemeris at a certain time, and determining numbers of key satellites, key satellite pairs and key satellite groups at a certain time; under H2 hypothesis, allocating the integrity risks by using the fault probability of satellites in key satellite pairs or key satellite groups, where the integrity risks allocated by using the fault probability of satellites in key satellite pairs or key satellite groups include integrity risks caused by dual-receiver fault and integrity risks caused by ranging source fault; under H0 and H1 hypotheses, allocating the integrity risks by using the fault probability of non-key satellites; making an integrity allocation table according to the integrity risk allocation under the H0, H1 and H2 hypotheses.

GBAS integrity risk allocation system based on key satellites

The present invention provides a BeiDou-based grid augmentation autonomous driving multi-level warning system comprising a Beidou Satellite Ground-based Augmentation system, user terminals and a Vehicles internet system, wherein the Beidou Satellite Ground-based Augmentation system comprises Beidou grid reference stations, a data processing system and a data broadcast system; the user terminal comprises an in-vehicle receiver and a calculating chips. The present invention can reduce the occurrence of traffic accidents and reduce the loss of life and property.

Beidou-based grid augmentation autonomous driving multi-level warning system

A dynamic baseline position domain monitoring system based on satellite navigation and inertial navigation is used to perform a method, including: a) determining a coordinate system and a transformation matrix; b) calculating a theoretical coordinate value of an antenna baseline vector in a earth-centered earth-fixed coordinate system during the movement of a base station carrier; c) determining the number of antenna baseline vectors to be monitored; d) solving the measurement values of the antenna baseline vectors; e) calculating the position domain error of an antenna baseline vector change rate in three directions of x, y and z at epoch k, and normalizing the position domain errors to obtain a normalized value of the position domain errors; f) obtaining the a cumulative sum; g) comparing the cumulative sum with an error monitoring threshold value, and issuing an integrity risk alarm.

Dynamic baseline position domain monitoring system

The present invention provides a calculation method for visual navigation integrity monitoring. With the method, by use of an appropriate visual positioning model, a mathematical algorithm and rich navigation measurements, the positioning accuracy and availability of positioning results are improved, and the problem of insufficient performance of satellite integrity algorithms caused by impossible guarantee of availability of a GNSS in complex environments is solved, which is helpful to realize aircraft accurate approach and automatic landing and of great significance to ensure the safety of aviation flight.

Calculation method for visual navigation integrity monitoring

The present invention provides an integrity analysis method based on a kinematic-to-kinematic relative positioning scenario, including the following steps: a) establishing a kinematic-to-kinematic relative positioning model, and inputting navigation data; b) calculating a float solution of an integer ambiguity; c) detecting and correcting cycle slips based on a total electron content rate; d) calculating a probability of correct fix and a probability of incorrect fix for the integer ambiguity; e) determining a fault to be detected and a satellite fault probability;calculating a standard deviation &#x3b4;_(v|CF) and a position domain deviation b_m; and g) calculating an integrity risk value of a carrier phase. The present invention provides an integer ambiguity calculation algorithm for a kinematic-to-kinematic positioning system in the case of a long baseline, to calculate carrier phase integrity.

Integrity analysis method based on kinematic-to-kinematic relative positioning scenario

The present invention provides a LDACS-based air-ground cooperative positioning method. According to the method, on the basis of LDACS, users are classified into super-high-altitude users, high-altitude users, and low-altitude users, and air-ground cooperative positioning is implemented through information exchange among the users at the three levels. Meanwhile, a new fault mode and an integrity hazard are introduced into the method. Therefore, the present invention further provides a method for monitoring the integrity of a LDACS-based air-ground cooperative positioning method, including a fault detection algorithm and a protection level solving method; and proposes a method for evaluating the complexity of integrity monitoring. The LDACS-based air-ground cooperative positioning method provided in the present invention well solves the problem of the shortage of APNT services in poor terrain conditions, making the positioning results more accurate.

LDACS-based air-ground cooperative positioning and integrity monitoring method

The present invention provides a ground-based augmentation system capable of predicting a tropospheric refractive index with high precision. The system includes a ground base station and an airborne receiver. The ground base station includes a ground acquisition device, a processor, and a transmitter. The ground acquisition device is configured to acquire meteorological parameters of a plurality of years, and use the acquired meteorological parameters as historical data. The processor is configured to call the historical data and establish a back propagation (BP) neural network to predict a refractive index. The transmitter is configured to send the refractive index predicted by the processor to the airborne receiver. With the present invention, the tropospheric refractive index is predicted for different weather conditions, thus improving the precision of tropospheric refractive index prediction.

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Beijing, China

Yanbo Zhu