Unmanned Aerial Vehicle Data Link Research Articles

Adaptive EMS Test Design Method on UAV Data Link Based on Bayesian Optimization

The complex electromagnetic environment makes the electromagnetic susceptibility (EMS) test challenging for the unmanned aerial vehicle (UAV) data link. The EMS test can be regarded as an optimization problem to obtain the maximum signal-to-interference ratio that makes the data link losing lock. In this article, we proposed an adaptive EMS test design method based on Bayesian optimization to expand the ability of the EMS test toward the UAV data link. The sensitive electromagnetic interference parameters can be automatically searched according to the adaptive test design method. The Gaussian process is used as the surrogate model for the EMS threshold. Besides, acquisition functions are discussed, including the probability of improvement, expected improvement, and upper confidence bound to balance the exploration and exploitation. Then, two test examples are applied to verify the adaptive test design method. Compared with the traditional EMS test methods, the proposed method introducing Bayesian optimization into the EMS test design can significantly improve the test efficiency and achieve an excellent human-in-the-loop effect.

EMI Threat Assessment of UAV Data Link Based on Multi-Task CNN

In this work, a multi-task convolutional neural network with multi-input (MIMT-CNN) is proposed for electromagnetic interference (EMI) signals recognition and electromagnetic environment risk evaluation of the data link of unmanned aerial vehicle (UAV). The visualized performance parameters, short-time Fourier transform (STFT) spectrograms, and constellation diagrams are obtained by experiment on the electromagnetic susceptibility of UAV’s datalink. In particular, the constellation diagram is further enhanced by calculating the density distribution of sampling points to obtain the normalized density constellation. Taking the above different categories of images as the input of the expected model, the multi-element and high correlation EMI features are extracted and fused in the MIMT-CNN. Besides, the structure of series-parallel connection is adopted in the trained model and the Bayesian optimization is also used to select hyperparameters. In this case, the perception model with higher reliability can be obtained. On this basis, the performance and complexity of the obtained model with different input channels are compared. The results show that with the input of constellation diagram, especially the normalized density constellation, can significantly improve the accuracy of the model. Besides the normalized density constellation, the model with visualized performance parameters and STFT spectrogram as inputs has a much better performance.

Prediction on EMS of UAV's Data Link Based on SSA-Optimized Dual-Channel CNN

In this article, a novel method is presented for electromagnetic interference (EMI) perception and electromagnetic susceptibility (EMS) assessment of an unmanned aerial vehicle (UAV) against interference. A large number of in-phase and quadrature data of the UAV's data link and their corresponding critical EMI signal were collected by the equivalent injection test method. After visualization and preprocessing of the in-phase and quadrature data, the obtained time–frequency spectrum and the data-link state parameter histogram were joined to further preprocess as the input of the model. A dual-channel convolutional neural network optimized by a sparrow search algorithm (SSA-DCNN) was proposed to predict the EMS of the data link of the UAV. The proposed method can not only avoid manual extraction of data features but also improve the intelligence level of EMI perception and safety evaluation on UAVs. The performance of the dual-channel convolutional neural network is compared with that of the SSA-DCNN method under different optimization algorithms. The results show that the SSA-DCNN model can significantly enhance the convergence speed and prediction accuracy of the training process compared with the dual-channel convolutional neural network. Besides, among the optimization algorithms, the stochastic gradient descent with momentum applied to the SSA-DCNN model shows a better performance.

GPR-Based EMI Prediction for UAV's Dynamic Datalink

The datalink of an unmanned aerial vehicle (UAV) is vulnerable to external electromagnetic interference (EMI). The characteristic parameters of the EMI signal can be definitively detected by a developed monitoring platform mounted on the UAV, but it is impossible to determine the lost-link thresholds of the datalink in any state by experiment because the state of the datalink varies dynamically with the flight distance and the UAV's attitudes. In this case, whether a certain state of the UAV's datalink will be interrupted or not by the EMI cannot be evaluated. In this article, a method of EMI prediction for the UAV's dynamic datalink based on the Gaussian process regression (GPR) is proposed, two indicators, including the interfering frequency and the operation signal power of the datalink, are taken as the training inputs, and the lost-link thresholds of the datalink obtained by the EMI injection test are taken as the training targets. The results show that this method can effectively fit the training samples and determine a 95% confidence interval of the predictive outputs, which has a low predictive error, less than 2.2 dB. Compared with the methods of the layer recurrent neural network and support vector machine, the GPR method has higher predictive accuracy and a stronger generalization ability. Therefore, the detected EMI characteristic parameters can be used as new input samples to predict the lost-link thresholds in any condition. On this basis, the EMI margin can be calculated to evaluate the degree of the anti-EMI redundancy of the UAV's datalink, which can be used for the active adaptation of the UAV's datalink to EMI in the future.

Research Progress of Anti-jamming Technology of Unmanned Aerial Vehicle(UAV) Data Link

An high-speed stealth UAV will be developed by an aviation research institute. Data link is an important part of UAV system. In order to have a deeper understanding of data link system, this paper was made through studying many recent academia papers. The basic composition and working principle of UAV data link system was introduced in this paper, the current UAV data link interference and anti-interference technology was expounded, the key problems faced by the development of UAV data link anti-interference technology were summarized, and the future development trend of UAV data link anti-interference technology was pointed out.

Simulation Research on Transmission Performance of UAV Data Link in Multipath Channel

Low elevation Angle is the common working environment of Unmanned Aerial Vehicle (UAV) data link. Naturally, data link transmission performance will be affected by White Gaussian Noise (WGN). Besides, multipath interference is more characteristic and usually more harmful. Taking Phase Shifting Keying (PSK) modulation system commonly used in data link as the object and typical UAV data link point-to-point configuration as the prototype, this paper analyzes the transmission principle of this system and the characteristics of multipath channel transmission, and then establishes the simulated transmission model of measurement and control communication link in multipath channel on this basis. Through simulation experiment, part of the simulation data and conclusions are given. According to the paper, increasing the link level redundancy design is not the fundamental measure to solve multipath fading. And the paper suggests that in order to improve the transmission performance of data link in multipath channel, it is feasible to add adaptive equalization technology at the level of signal processing.

An Anti-Interference Scheme for UAV Data Links in Air-Ground Integrated Vehicular Networks.

As one of the main applications of the Internet of things (IoT), the vehicular ad-hoc network (VANET) is the core of the intelligent transportation system (ITS). Air–ground integrated vehicular networks (AGIVNs) assisted by unmanned aerial vehicles (UAVs) have the advantages of wide coverage and flexible configuration, which outperform the ground-based VANET in terms of communication quality. However, the complex electromagnetic interference (EMI) severely degrades the communication performance of UAV sensors. Therefore, it is meaningful and challenging to design an efficient anti-interference scheme for UAV data links in AGIVNs. In this paper, we propose an anti-interference scheme, named as Mary-MCM, for UAV data links in AGIVNs based on multi-ary (M-ary) spread spectrum and multi-carrier modulation (MCM). Specifically, the Mary-MCM disperses the interference power by expanding the signal spectrum, such that the anti-interference ability of AGIVNs is enhanced. Besides, by using MCM and multiple-input multiple-output (MIMO) technologies, the Mary-MCM improves the spectrum utilization effectively while ensuring system performance. The simulation results verify that the Mary-MCM achieves excellent anti-interference performance under different EMI combinations.

Research on ultra-wideband electromagnetic pulse irradiation effect and protection method of Unmanned Aerial Vehicle

The data link is an important guarantee for the Unmanned Aerial Vehicle (UAV) equipment to complete its battlefield functions. Its anti-electromagnetic pulse interference capability directly affects the airborne communication security. Ultra-wideband (UWB) electromagnetic pulse has become an important source of electromagnetic interference due to its high power, wide frequency band and wide interference target. In order to verify the reliability of UAV data link communication under UWB electromagnetic pulse irradiation conditions, the UWB electromagnetic pulse irradiation effect experiment of UAV was carried out, and the mechanism of “lost lock” effect of UAV data link was analyzed. The experimental results show that when the UWB electromagnetic pulse irradiation intensity reaches 140 kV / m, it will cause hardware damage to the UAV, and found that its internal sensitive device low noise amplifier is damaged. In response to this, the comprehensive design of the electromagnetic protection measures for the UAV was carried out, laying the foundation for the next step to strengthen the electromagnetic protection of the UAV.

Investigation on Effects of HPM Pulse on UAV's Datalink

Unmanned aerial vehicle (UAV) is likely to be interfered by high-power microwave (HPM) pulse, especially its datalink. To investigate the effects of HPM pulse on the datalink of a UAV in a dynamic flight scenario, a tracking interference model for an HPM source toward a UAV is proposed, as well a dynamic flight model is also built to determine the HPM reception of the UAV's datalink. In order to predict the possible effects of HPM on the datalink, the tests on a certain type of UAV's datalink are carried out in the presence of HPM with its carrier frequency in L -, S - and C -band, respectively. The results show that the electromagnetic interference (EMI) can easily enter the receiver via front-door when the carrier frequency of the HPM falls into the operating frequency band of the datalink, which will lead to a permanent physical damage. However, when the carrier frequency deviates from the operating frequency band of the datalink, the EMI couples into the incomplete shielded power line via back-door and generates a high-voltage signal at the power port, resulting in a transient lost-link effect or even a functional failure of the datalink due to its abnormal electric power supply. Finally, some suggestions are put forward to improve the UAV's adaptability in the HPM environment.

Predicting the Health Status of an Unmanned Aerial Vehicles Data-Link System Based on a Bayesian Network

Unmanned aerial vehicles (UAVs) require data-link system to link ground data terminals to the real-time controls of each UAV. Consequently, the ability to predict the health status of a UAV data-link system is vital for safe and efficient operations. The performance of a UAV data-link system is affected by the health status of both the hardware and UAV data-links. This paper proposes a method for predicting the health state of a UAV data-link system based on a Bayesian network fusion of information about potential hardware device failures and link failures. Our model employs the Bayesian network to describe the information and uncertainty associated with a complex multi-level system. To predict the health status of the UAV data-link, we use the health status information about the root node equipment with various life characteristics along with the health status of the links as affected by the bit error rate. In order to test the validity of the model, we tested its prediction of the health of a multi-level solar-powered unmanned aerial vehicle data-link system and the result shows that the method can quantitatively predict the health status of the solar-powered UAV data-link system. The results can provide guidance for improving the reliability of UAV data-link system and lay a foundation for predicting the health status of a UAV data-link system accurately.

Simulation of dynamic electromagnetic interference environment for Unmanned Aerial Vehicle data link

In order to test the anti-interference ability of an Unmanned Aerial Vehicle (UAV) data link in a complex electromagnetic environment, a method for simulating the dynamic electromagnetic interference of an indoor wireless environment is proposed. This method can estimate the relational degree between the actual face of an UAV data link in an interface environment and the simulation scenarios in an anechoic chamber by using the Grey Relational Analysis (GRA) theory. The dynamic drive of the microwave instrument produces a real-time corresponding interference signal and realises scene mapping. The experimental results show that the maximal correlation between the interference signal in the real scene and the angular domain of the radiation antenna in the anechoic chamber is 0.959 3. Further, the relational degree of the Signal-to-Interference Ratio (SIR) of the UAV at its reception terminal indoors and in the anechoic chamber is 0.996 8, and the time of instrument drive is only approximately 10 μs. All of the above illustrates that this method can achieve a simulation close to a real field dynamic electromagnetic interference signal of an indoor UAV data link.

Studies on Novel Anti-jamming Technique of Unmanned Aerial Vehicle Data Link

Based on the M-ary spread spectrum (M-ary-SS), direct sequence spread spectrum (DS-SS), and orthogonal frequency division multiplex (OFDM), a novel anti-jamming scheme, named orthogonal code time division multi-subchannels spread spectrum modulation (OC-TDMSCSSM), is proposed to enhance the anti-jamming ability of the unmanned aerial vehicle (UAV) data link. The anti-jamming system with its mathematical model is presented first, and then the signal formats of transmitter and receiver are derived. The receiver's bit error rate (BER) is demonstrated and anti-jamming performance analysis is carried out in an additive white Gaussian noise (AWGN) channel. Theoretical research and simulation results show the anti-jamming performance of the proposed scheme better than that of the hybrid direct sequence frequency hopping spread spectrum (DS/FH SS) system. The jamming margin of the OC-TDMSCSSM system is 5 dB higher than that of DS/FH SS system under the condition of Rician channel and full-band jamming, and 6 dB higher under the condition of Rician channel environment and partial-band jamming.