Source Unmanned Aerial Vehicle Research Articles

UAVs-assisted passive source localization using robust TDOA ranging for search and rescue

Estimating the location of a target in search-and-rescue operations is quite challenging when the target is not responding. Therefore, in this paper, we investigate the passive target localization problem using mobile unmanned aerial vehicles (UAVs), where multiple mobile UAVs receive the time-difference-of-arrival (TDOA) measurements from the source UAV. Unlike traditional TDOA for static UAVs, the problem becomes more challenging when considering the mobility of UAVs. Therefore, we propose a novel TDOA model for target localization with mobile UAVs. We also measure the performance limit inequality between its Cramer-Rao lower bound (CRLB) and the mean-squared error (MSE).

An Adaptive Joint Bilateral Interpolation-Based Color Blending Method for Stitched UAV Images

Given a source UAV (unmanned aerial vehicle) image Is and a target UAV image It, it is a challenging problem to correct the color of all target pixels so that the subjective and objective quality effects between Is and It can be as consistent as possible. Recently, by referring to all stitching color difference values on the stitching line, a global bilateral joint interpolation-based (GBJI-based) color correction method was proposed. However, because all stitching color difference values may contain aligned and misaligned stitching pixels, the GBJI-based method suffers from a perceptual artifact near the misaligned stitching pixels. To remedy this perceptual artifact, in this paper, we propose an adaptive joint bilateral interpolation-based (AJBI-based) color blending method such that each target pixel only adaptively refers to an adequate interval of stitching color difference values locally. Based on several testing stitched UAV images under different brightness and misalignment situations, comprehensive experimental results demonstrate that in terms of PSNR (peak signal-to-noise ratio), SSIM (structural similarity index), and FSIM (feature similarity index), our method achieves higher objective quality effects and also achieves better perceptual effects, particularly near the misaligned stitching pixels, when compared with the GBJI-based method and the other state-of-the-art methods.

Mobile jammer enabled secure UAV communication with short packet transmission

This paper studies a mobile jammer enabled secure unmanned aerial vehicle (UAV) communication network in the finite packet length scenario, where the external friendly jammer UAV will transmit jamming signal to deteriorate the quality of eavesdropping channel, and help to improve the secure communication performance of the source UAV. Specifically, an average effective secrecy rate (AESR) maximization problem is formulated by jointly designing the trajectories and transmit power of the source/jammer UAV subject to the UAVs’ mobility constraints and power constraints. It is also verified that there exists a unique optimal packet error rate to maximize the AESR. The formulated problem is mathematically intractable, as it is nonconvex and involves coupled optimization variables. Therefore, we first decompose the trajectories and power optimization problem into four non-convex subproblems, and then transform them into standard convex problems by applying first-order Taylor expansion. Then, an efficient alternating optimization algorithm for AESR problem based on Bisection method and successive convex approximation (SCA) technology is presented by addressing the five subproblems iteratively. Simulation results are provided to verify that our proposed scheme can obtain considerable better AESR gain compared to other four benchmark schemes.

Secure transmission in satellite-UAV integrated system against eavesdropping and jamming: A two-level stackelberg game model

Aiming at the physical layer security (PLS) secure transmission existing in the information backhaul link of the satellite-UAV integrated (SUI) network, a two-layer Stackelberg game model (TSGM) that can resist full-duplex (FD) eavesdropping and jamming attacks is proposed. The confrontation relationship between the UAV network and the attacker is established as the first layer Stackelberg game. The source UAV adjusts its own transmission power strategy according to the attacker's jamming strategy to resist malicious jamming attacks. The internal competition and cooperation relationship in UAV network is modeled as the second layer Stackelberg game, and the optimal cooperative UAV transmits jamming signal to the attacker to resist malicious eavesdropping attacks. Aiming at the "selfishness" of UAV nodes, a price incentive mechanism is established to encourage UAV to actively participate in cooperation, so as to maximize the advantages of cooperative communication. For the proposed TSGM, we construct the utility function and analyze the closed equilibrium solution of the game model, and design a three-stage optimal response iterative (TORI) algorithm to solve the game equilibrium. The simulation results show that the proposed TSGM can effectively increase the utility of the source UAV and improve the enthusiasm of cooperation compared with other power control models.

Optimal Relay Network for Aerial Remote Inspections.

Unmanned aerial vehicles (UAVs), in particular multirotors, are becoming the de facto tool for aerial sensing and remote inspection. In large industrial facilities, a UAV can transmit an online video stream to inspect difficult-to-access structures, such as chimneys, deposits, and towers. However, the communication range is limited, constraining the UAV operation range. This limitation can be overcome with relaying UAVs placed between the source UAV and the control station, creating a line of communication links. In this work, we assume the use of a digital data packet network technology, namely WiFi, and tackle the problem of defining the exact placement for the relaying UAVs that creates an end-to-end channel with maximal delivery of data packets. We consider asymmetric communication links and we show an increase as large as 15% in end-to-end packet delivery ratio when compared to an equidistant placement. We also discuss the deployment of such a network and propose a fully distributed method that converges to the global optimal relay positions taking, on average, times the time taken by a centralized method.

Bearings only passive location of UAV in formation flight based on computer simulation

Azimuth-only target location and tracking based on image vision is a passive target location method, which has become a research hotspot of target tracking at present. Aiming at the problem of bearings only passive location of UAV, this paper establishes a geometric location model of UAV bearings, and finally realizes bearings only passive location of UAV. This paper first analyzes the data and establishes a data flow chart. By defining the position of the UAV, the positioning model of the UAV with a passive receiving signal is established. GeoGebra is used to visualize the data. This paper can determine that there are five positioning models of UAV position deviation, namely, inside and outside the circumference, left and right of the circumference, without deviation. Then, by adjusting the position of the received signal source UAV, this paper constructs a visual mathematical model by classification, discussion, arrangement, and combination, and determines that two more UAVs are needed to achieve effective positioning of the UAV. At last, GeoGebra is used to make assumptions about the position adjustment of the UAV, and Matlab is used to simulate it to obtain an ideal state model.

Distributed reinforcement learning based framework for energy-efficient UAV relay against jamming

Unmanned aerial vehicle (UAV) network is vulnerable to jamming attacks, which may cause severe damage like communication outages. Due to the energy constraint, the source UAV cannot blindly enlarge the transmit power, along with the complex network topology with high mobility, which makes the destination UAV unable to evade the jammer by flying at will. To maintain communication with a limited battery capacity in the UAV networks in the presence of a greedy jammer, in this paper, we propose a distributed reinforcement learning (RL) based energy-efficient framework for the UAV networks with constrained energy under jamming attacks to improve the communication quality while minimizing the total energy consumption of the network. This framework enables each relay UAV to independently select its transmit power based on historical state-related information without knowing the moving trajectory of other UAVs as well as the jammer. The location and battery level of each UAV need not be shared with other UAVs. We also propose a deep RL based anti-jamming relay approach for UAVs with portable computation equipment like Raspberry Pi to achieve higher and faster performance. We study the Nash equilibrium (NE) and the performance bounds based on the formulated power control game. Simulation results show that the proposed schemes can reduce the bit error rate (BER) and reduce energy consumption of the UAV network compared with the benchmark method.

An agent-based self-protective method to secure communication between UAVs in unmanned aerial vehicle networks

UAVNs (unmanned aerial vehicle networks) may become vulnerable to threats and attacks due to their characteristic features such as highly dynamic network topology, open-air wireless environments, and high mobility. Since previous work has focused on classical and metaheuristic-based approaches, none of these approaches have a self-adaptive approach. In this paper, the challenges and weaknesses of previous methods are examined in the form of a table. Furthermore, we propose an agent-based self-protective method (ASP-UAVN) for UAVNs that is based on the Human Immune System (HIS). In ASP-UAS, the safest route from the source UAV to the destination UAV is chosen according to a self-protective system. In this method, a multi-agent system using an Artificial Immune System (AIS) is employed to detect the attacking UAV and choose the safest route. In the proposed ASP-UAVN, the route request packet (RREQ) is initially transmitted from the source UAV to the destination UAV to detect the existing routes. Then, once the route reply packet (RREP) is received, a self-protective method using agents and the knowledge base is employed to choose the safest route and detect the attacking UAVs. The proposed ASP-UAVN has been validated and evaluated in two ways: simulation and theoretical analysis. The results of simulation evaluation and theory analysis showed that the ASP-UAS increases the Packet Delivery Rate (PDR) by more than 17.4, 20.8, and 25.91%, and detection rate by more than 17.2, 23.1, and 29.3%, and decreases the Packet Loss Rate (PLR) by more than 14.4, 16.8, and 20.21%, the false-positive and false-negative rate by more than 16.5, 25.3, and 31.21% those of SUAS-HIS, SFA and BRUIDS methods, respectively.

Cache-enabled physical-layer secure game against smart uAV-assisted attacks in b5G NOMA networks

This paper investigates cache-enabled physical-layer secure communication in a no-orthogonal multiple access (NOMA) network with two users, where an intelligent unmanned aerial vehicle (UAV) is equipped with attack module which can perform as multiple attack modes. We present a power allocation strategy to enhance the transmission security. To this end, we propose an algorithm which can adaptively control the power allocation factor for the source station in NOMA network based on reinforcement learning. The interaction between the source station and UAV is regarded as a dynamic game. In the process of the game, the source station adjusts the power allocation factor appropriately according to the current work mode of the attack module on UAV. To maximize the benefit value, the source station keeps exploring the changing radio environment until the Nash equilibrium (NE) is reached. Moreover, the proof of the NE is given to verify the strategy we proposed is optimal. Simulation results prove the effectiveness of the strategy.

Task-Driven Relay Assignment in Distributed UAV Communication Networks

In this paper, we study the distributed relay assignment problem in multi-channel multi-radio unmanned aerial vehicle (UAV) communication networks. Multi-UAVs are driven by the overall task and fly in certain formation, where UAVs with different tasks have various transmission requirements. Source UAVs equipped with multi-radio can select more than one relay radios to achieve high data rate, and each relay radio can be shared by multiple source UAVs. We construct distributed game models to promote the global transmission performance by self-organizing coordination among UAVs. Specifically, the channel competition relationship between relay UAVs is modeled as a congestion game model, while the task-driven relay selection among UAVs is modeled as a many-to-many matching market without substitutability. With the proposed game models, the optimizing of local optimized process will lead to the improvement of global transmission results. After that, we design algorithms for the stable and changeable topology structures, respectively. Based on the given formation shape of UAVs, a learning matching algorithm is proposed to reach the optimum result with a large probability. A fast potential matching algorithm is propose to deal with the topological change of UAV networks. We prove that two proposed algorithms can both achieve the stable matching results. Simulation results show that the proposed relay assignment approaches yield good performances in terms of the global transmission satisfaction and fairness. Particularly, the result of the learning algorithm is close to the global optimum and the fast potential matching approach is robust to the perturbation of UAV networks.

Energy-Efficient Cooperative Secure Transmission in Multi-UAV-Enabled Wireless Networks

This paper investigates a multiple unmanned aerial vehicles (UAVs) enabled cooperative secure transmission scheme in the presence of multiple potential eavesdroppers. Specifically, multiple source UAVs (SUAVs) send confidential information to multiple legitimate ground users, and in the meantime, multiple jamming UAVs cooperatively transmit interference signals to multiple eavesdroppers in order to improve the legitimate users’ achievable secrecy rate. By taking into account the limited energy budget of UAV, our goal is to maximize the system secrecy energy efficiency (SEE), namely the achievable secrecy rate per energy consumption unit, by jointly optimizing the UAV trajectory, transmit power, and user scheduling under the constraints of UAV mobility as well as the maximum transmit power. The resulting optimization problem is shown to be a non-convex and mixed-integer fractional optimization problem, which is challenging to solve. We decompose the original problem into three sub-problems, and then, an efficient iterative algorithm is proposed by leveraging the block coordinate descent method and Dinkelbach method in combination with successive convex approximation techniques. Simulation results show that the proposed scheme outperforms the other benchmarks significantly in terms of the system SEE.

Opportunistic cooperative TDMA scheme for FANETs

Practical and efficient routing protocols for networks of unmanned aerial vehicles (UAVs) have rapidly grown into a research hotspot in future advanced wireless communication. This paper studies a TDMA-based opportunistic cooperative relaying (OCR-TDMA) MAC scheme for Flying Ad-Hoc Networks (FANETs), which is applied in a two-hop relay network composed of source UAV, relaying UAV, destination UAV and helper UAVs. Here, helper UAVs are different with the default relaying UAV, and only help forwarding relay packets when certain conditions are met, which balances fairness and high efficiency. This paper proposes a method to calculate the throughput of OCR-TDMA. The theoretical analysis results and simulation results match well, and show attractive performance gain against CR-TDMA. Markablely, OCR-TDMA can perform well even in hostile communication environment, in which CR-TDMA is almost out of work.

MDRMA: Multi-data rate mobility-aware AODV-based protocol for flying ad-hoc networks

The most recent decade has seen a developing enthusiasm for the utilization of Unmanned Aerial Vehicles (UAVs) for different services and applications. UAVs, or as known as drones, have appeared to be productive in finishing complex errands when sorted out as ad hoc connected groups, thereby bringing into existence a Flying Ad hoc Network (FANET). Owing to its specific characteristics such as high mobility, rapid topology changes, and frequent link failures, FANETs bring further challenges into these networks. Therefore, developing an efficient routing protocol over FANETs is a very challenging matter and consequently triggered the attention of a lot of current researchers. In this article, we propose a Multi Data Rate Mobility Aware (MDRMA) protocol in which novel routing and power controlled mechanisms have been suggested. Basically, MDRMA protocol is considered as a major extension of Mobility Aware Dual Phase Ad-hoc on-demand Distance Vector with Adaptive Hello Messages (MA-DP-AODV-AHM) protocol. Particularly, in MDRMA-Routing algorithm, the establishment of routes is not arbitrarily but rather is conditioned upon the achievement of certain requirements which can be extracted from the positive answers of the questions follow. Is that intermediate UAV able of affording the possible transmission rate requested by the source UAV? Are the transmitting and receiving UAVs not thrifting away from each other? Does the speed of that intermediate UAV not exceed a certain threshold? Upon the efficient deal of prior concerns, MDRMA-Routing algorithm guarantees establishing stable routes with fast data forwarding wireless links. Not only to this extent, MDRMA-Power controlled algorithm also adds some modifications on 802.11b standard, explicitly on RTS/CTS collision avoidance technique, to maintain the minimum transmission power required by a transmitting UAV for a successful reception of packets at target UAV and at a desired data transmission rate bearing in mind the receiver sensitivity and signal-to-interference-noise ratio threshold, thereby enforcing fast data forwarding. The performance of our protocol has been evaluated in the perspectives of end-to-end delay, control overhead, and packet delivery ratio using NS3 simulator in which enormous simulations have been conducted under the base of UAVs' density, packet rate and constant bit rate connections. Simulation results summarize that MDRMA contributes efficiently in mitigating the network instability through generating fast and stable routes and reducing link failures. MDRMA has proved further its superiority over MA-DP-AODV-AHM protocol.

Resource-Optimized Multiarmed Bandit-Based Offload Path Selection in Edge UAV Swarms

This paper looks into the problem of a decentralized data offloading within an edge unmanned aerial vehicle (UAV) swarm to mitigate the complexities of a single UAV continually generating and processing large application-specific data. The mobile edge UAVs considered here are multirotor types having constrained energy and processing power, which makes long-term handling of large data volumes impossible for standalone UAVs. The load mitigation is carried out by offloading data from a source UAV to other swarm members with sufficient energy and processing requirements. In this paper, we focus on selecting the most optimal multihop path through the UAVs concerning available energies and processing resources, which can survive the duration of the data offload between the source and a target UAV. We formulate a multiarmed bandit-based offload path selection scheme, which selects the most energy and processing optimized multihop path between a source and a target UAV. Upon comparison of our scheme against the naive shortest path approach, we observe that our approach results in significant savings of collective network energies, even for long operational durations.

Is Hop-by-Hop Always Better Than Store-Carry-Forward for UAV Network?

As energy supply on Unmanned Aerial Vehicle (UAV) is limited, energy efficient data transmission in UAV networks would be of great concern to the researchers. Nevertheless, UAV networks exhibit strong dynamic nature compared to ordinary Mobile Ad hoc Network (MANET), it is not rare that some nodes will be disjoint from other nodes from time to time. Under such circumstance, ordinary hop-by-hop routing schemes can not be used anymore, for there is no route existed from source to destination. Some solutions use store-carry-forward (SCF) routing to facilitate end to end data transmission. However, when should we use SCF routing, when we should use hop-by-hop routing if we taking energy into consideration? Is hop-by-hop routing always better than SCF? If it is good or not when the hop-by-hop routing is combined with the SCF routing? All these questions need to be answered. In this paper, we answered above questions by proposing three types of minimum energy consumption models of hop-by-hop routing, and two SCF routing models. We compared all these models and considered four tactics of combination modes for the transmissions in a rotary-wing UAV network. The researches show that two tactics have better performance than other modes in energy saving capabilities by reducing 70% at most with the hop-by-hop routing, and the transmission time of combination modes are in same scale compared with hop-by-hop routing. The two tactics are appropriate for different UAV networks respectively, in which the source UAV can or cannot get the GPS information of relay UAVs in the route. The research conclusion can also be used for the transmissions in a fixed-wing UAV network by modifying the energy consumption models of fixed wing UAV, which is different from rotary wing UAVs.

A Course-Aware Opportunistic Routing Protocol for FANETs

In recent years, unmanned aerial vehicles (UAVs) have gained popularity in various applications and services in both the military and civilian domains. Compared with the single-UAV scenario, flying ad hoc networks (FANETs) consisting of ground stations (GSs) and UAVs have the advantages of flexible configuration and wide coverage. However, due to significant mobility and highly dynamic topology, designing reliable and efficient routing protocols for FANETs is a challenging task. In this paper, we consider a network that comprises multiple flying UAVs and GSs to transfer messages by multi-hop relaying. We propose a routing protocol, named course-aware opportunistic routing for FANETs (CORF). The UAVs cooperatively exchange aeronautical data with others. The source UAV node (SUN) calculates the transfer probabilities to different neighbors by jointly considering the positions of its neighbors and the destination node. Based on the direction information and the transfer probabilities, the SUN selects the next-hop relay nodes among the neighbor UAVs and GSs. This process continues until the destination node receives the message. The simulation results demonstrate that, the proposed CORF protocol achieves significant performance superiority as compared with the traditional protocols in terms of message delivery rate and network latency.

Mobile jammer-aided secure UAV communications via trajectory design and power control

To further promote the achievable average secrecy rate for UAV-ground communications, a UAV-aided mobile jamming strategy was proposed in this paper. Specifically, an additional cooperative UAV is employed as a mobile jammer to transmit the jamming signal to help keep the source UAV closer to the ground destination, thus establishing more favorable legitimate link and enhancing the secrecy performance. We aimed to maximize the achievable secrecy rate by jointly optimizing the trajectories and transmit power of both source UAV and jammer UAV. To solve the considered non-convex optimization problem, we presented a block coordinate descent based iterative algorithm to address a sequence of approximated convex problems for the optimized parameter block by block to find a local optimal solution. Numerical results verify that the proposed algorithm can achieve significant secrecy rate gain compared to all the benchmark schemes.

Energy efficient multi-antenna UAV-enabled mobile relay

In this paper, we study an energy efficient multi-antenna unmanned aerial vehicle (UAV)-enabled half-duplex mobile relaying system under Rician fading channels. By assuming that the UAV follows a circular trajectory at fixed altitude and applying the decode-and-forward relaying strategy, we maximize the energy efficiency by jointly designing beamforming, power allocation, circular radius and flight speed, subject to the sum transmit power constraint on source node and UAV relay node. First, we maximize the end-to-end signal-to-noise ratio by jointly designing beamforming and statistical power allocation. Based on the obtained beamforming and power allocation results, we then obtain a semi closed-form expression of energy efficiency, and finally maximize energy efficiency by optimizing flight speed and circular radius, allowing optimal circular radius to be obtained via numerical computation. Numerical results demonstrate that the proposed scheme can effectively enhance the system energy efficiency.

Using low cost open source UAVs for marine wild life monitoring - Field Report

In this paper we report results on the use of low cost, open source Unmanned Aerial Vehicles (UAV) for detecting and tracking hammerhead sharks using a digital camera payload. With the prevailing increase in affordability of Unmanned Aerial Systems (UAS) these have gained a widespread appeal and use in civilian, military and academic research scenarios. Moreover these systems have become easier to setup and deploy allowing their use in projects or activities with more limited means of funding. Still, the challenge of successfully meeting the end-user's demands with an easy-to-use, low cost operational package while avoiding over-fitting issues remains. This paper explores the applicability and successfulness of an existing low cost UAS solution in tackling maritime based environmental studies, while testing its scalability potential. Furthermore while relying upon an established tool-chain, different payload configurations were fitted into the UAV. After a series of real flight tests the end-user's required data was recovered distilled and analysed. End-user feedback demonstrated an overwhelming satisfaction with UAS's capacity to meet the required goals while retaining its modularity and affordability intact.