Implementation of Automatic Aircraft Tracking with RTL-SDR

Operations in the Next Generation Air Transportation System (NextGen) are planned to have a reduced dependency on primary surveillance radar and use Automatic Dependent Surveillance - Broadcast (ADS-B) to provide aircraft state information to Air Traffic Control (ATC) and onboard collision detection and avoidance systems. With the ongoing integration of Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS), ADS-B is expected to become the main surveillance input to UAS collision avoidance. Traffic Alert and Collision Avoidance System (TCAS) is unable to meet requirements in terms of adaptability to future operations with reduced separation margins, addition of new user groups (e.g., UAS), and support of additional surveillance inputs. Airborne Collision Avoidance System (ACAS X) is being designed to meet these requirements and to increase surveillance, alerting, and resolution performance. The RTCA has released Minimum Operational Performance Standards (MOPS) to provide system and operational performance characteristics that ADS-B must provide. This paper analyzes recorded ADS-B data from test flights that were performed in the Continental U.S. (CONUS) and verifies measured performance with specified operational characteristics in terms of coverage, accuracy, and integrity.

Technological independence is important for every country in global competition. One of the technological advancements developed by the Indonesian government through BPPT is Automatic Dependent Surveillance Broadcast (ADS-B) type in, which functions as a flight monitoring system. The Indonesian Air Force (TNI AU) through Depohar 50 (Depot Maintenance 50) has also developed ADS-B type in, which is currently deployed in six radar units known as the Flight Monitoring System (FMS) Mode-S. Accordance with government regulations (Minister of Transportation Regulation No. 81 of 2017), the government has mandated the use of ADS-B for flight safety. ADS-B has two types, in and out. In the TNI AU, ADS-B out is installed on aircraft such as Grob, KT-1, and Cessna, while ADS-B in is installed on Weibel radar. However, since ADS-B is not yet installed on TNI AU aircraft, flight data from the Air Traffic Control (ATC) was communicated to the pilots, hence, they can be aware of the air traffic situation. Furthermore, due to the increasing air traffic, communication with ATC has become limited. A qualitative method was used in the development of the ADS-B type in TNI AU aircraft, and the previous ADS-B type in development could only be installed on the ground station. The information received from ADS-B on the aircraft was real-time air traffic, which helps pilots make decisions to enhance flight safety, such as reducing the risk of aircraft collisions. The use of this technology on TNI AU aircraft is important for improving flight safety and technological independence.

Application layer interoperability between the surveillance broadcast services system (SBSS) and automatic dependent surveillance - broadcast (ADS-B) avionics is a critical requirement for the next generation air transportation system (NextGen). Demonstrating compatibility between the SBSS and avionics requires the integration of diverse avionics tools, simulated environments tools, RF transmitter test sets, signal analyzers, SBSS equipment, and other receiving systems. ITT has developed a testbed that enables not only validation of the SBSS requirements and RTCA standards, but also provides a window into the user's perspective for various applications. The RF transmitter test set is particularly valuable for generating simulated aircraft flight patterns because it can produce 1090, UAT, and 1030 messages with dynamically programmable content. These ADS-B, Mode S, and ATCRBS messages stimulate SBSS behavior, resulting in transmissions that affect the information and system states held by avionics and air traffic control. A series of simulations with the SBSS and avionics in the loop are conducted and subsequently analyzed.

Automatic dependent surveillance-broadcast (ADS-B) is a very important communication and surveillance technology in air traffic control (ATC). In the future, more and more satellites will carry out ADS-B technology to perform a global coverage. In order to make full use of the resources in the satellite, this paper proposes a solution for satellite three-axis attitude determination using the ADS-B receiver. The principle of ADS-B-based attitude determination is presented first. On this basis, ADS-B-based methods are employed to solve the problem. To achieve a higher attitude determination precision, gyro is combined with the ADS-B receiver using a multiplicative extended Kalman filter (MEKF). Finally, a simulation is carried out and the result is presented.

In this paper, we develop a novel method to detect Global Navigation Satellite Systems (GNSS) spoofing for an Automatic Dependent Surveillance-Broadcast (ADS-B) equipped aircraft. The Federal Aviation Administration (FAA) has mandated [18] all civil aircraft to be ADS-B Out equipped by January 1, 2020. The ADS-B Out broadcast sent to Air Traffic Control (ATC) consists of the aircraft's position, velocity, and other aircraft-specific information, all of which being unencrypted, poses a serious integrity threat. With readily available ADS-B trackers [19], [20], a spoofer can accurately track an aircraft to generate a spoofed trajectory that can go undetected [11]. We propose a novel method to modulate the ADS-B Out position broadcast such that a spoofed trajectory generated using the modulated ADS-B will be detectable by comparing Inertial Navigation System (INS) positions against those obtained using the spoofed GNSS signal. The amplitude of ADS-B modulation is selected to exceed the nominal INS error covariance so that spoofing is observable. In this work, we analytically quantify the magnitude of ADS-B modulation that will be sufficient for spoofing detection. During scenarios of GNSS signal jamming and spoofing, reauthentication of a reacquired GNSS signal is necessary to maintain integrity. During a GNSS outage, given enough time, the INS solution drift will grow large enough such that the spoofed GNSS solution might be within the INS error covariance envelope and go undetected. For GNSS outage scenarios we propose continuous modulation of ADS-B position and analytically quantify the magnitude such that spoofing of the GNSS signal is detectable after signal is re-acquired.

Security analysis of the ADS-B implementation in the next generation air transportation system

Air traffic control nowadays mainly relies on radar based surveillance system and with the growth of air traffic, the problems of air transportation system is approaching its limit. The increase in the task of scheduling flights results in higher overall operation cost and pose higher rate of flight safety hazards. Thus, an upgrade from conventional air traffic management systems to the Next Generation Air Transportation (NextGen) System is required. The Automatic Dependent Surveillance Broadcast (ADS-B) modem is the key component of NextGen, which uses Global Navigation Satellite System (GNSS) to provide better accuracy of aircraft position. ADS-B continuously broadcasts information on altitude, position, identity, velocity, and other aircraft information to generate best picture for air traffic management. In this paper, the ADS-B modulator and demodulator have been developed using high-level RVC-CAL dataflow actor language, and automatically synthesized to C and Verilog/VHDL codes for hardware and software implementations. Results show that the performance of the proposed designs at high-level exceeds the minimum throughput requirement specified in the ADS-B standard by a factor of more than three.

ADS-B (Automatic Dependent Surveillance – Broadcast) involves broadcasting the latitude, longitude, altitude, velocity, identification and other information from on-board systems. Any suitable receiver may receive and process these broadcasted messages, which can be an ADS-B Ground Station which processes the ADS-B messages and generates aircraft reports to be used by Air Traffic Controllers.

In this paper, we present a fun way to teach digital communications in engineering schools. Through Software Defined Radios (SDR), we propose to the students of the Telecommunications Department of the ENSEIRB-MATMECA, Bordeaux INP to put into practice their skills in digital communications, signal processing, channel coding, etc. on real signals. More precisely, we guide them through a project, to decode the trajectories of aircraft by demodulating Automatic Dependent Surveillance-Broadcast (ADS-B) signals. In addition to the playfulness of this project, dealing with real signals also makes it possible to verify certain modelling assumptions such as the white and Gaussian noise character or the frequency non-selectivity of the channel disturbing the ADS-B signals. The novelty of our approach also lies on the collaborative aspect of this project. Students can test their implementation any time in class or at home by sharing with us their works which is merged on an always online server connected to a SDR hardware.

Millions of small Unmanned Aerial Systems (sUAS), or drones weighing less than 55 pounds, will fly in urban airspaces within a decade. This is in addition to goals for increased Urban Air Mobility (UAM): larger transportation UAS and piloted air vehicles, including air taxi service and innovative aviation designs to revolutionize transportation. A significant problem is the lack of current management systems for this extremely large volume of air traffic, composed of heterogeneous drone shapes, sizes, and onboard equipment capabilities, flying adjacent to larger UAM vehicles in spaces previously unoccupied by General Aviation (GA). Robust and resilient detection, identification, localization, and tracking of sUAS sharing UAM airspace is complicated by urban factors such as non-transmitting, non-cooperative drones. Exacerbating these challenges, current technological limitations and vulnerabilities in Global Positioning System (GPS), Automatic Dependent Surveillance-Broadcast (ADS-B), and Inertial Navigation Systems (INS) can pose safety and security threats. To streamline a vision of safe and secure sUAS-UAM shared airspace, we propose Drone Net, a UAS Traffic Management (UTM) network of multi-modal ground and flight instruments. Drone Net is an architecture fusing a network of passive visual and acoustic sensor nodes with active Radio Detection and Ranging (radar) and Light Detection and Ranging (lidar) sensing methods for UTM, designed for integration with existing Air Traffic Control (ATC) and future UAM systems. The purpose of the Drone Net system is to evaluate use of Electro-Optical/Infrared (EO/IR) and acoustic arrays networked within an urban UAS operating region such as uncontrolled Class-G and waiver-granted Class-D airspace. The Drone Net approach combines detection, tracking, and localization estimation from radar, ADS-B, and EO/IR such that the design is robust to sensor errors, sample loss, and spoofing or other types of attacks. The system experimental design allows for emulation of corrupted ADS-B, GPS, and INS data on our flight platform including capability to communicate with ground radar and EO/IR to recover from flight instrument major and minor malfunctions such that a Drone Net cooperative UAS can be engineered to be fail-safe and fail-secure. We hypothesize that the Drone Net network of rooftop sensors, shown below, provides this conceptualized fail-safe, fail-secure property based upon the combination of self-localization with backup and confirming data from the ground sensor network. Further, with ground-system sensor fusion as well as UTM flight plan and registration information fusion, the overall system can manage small UAS that are both compliant and non-compliant alongside GA and UAM more safely than a single mode like ADS-B alone. To test our hypothesis, we envision two experiments this year. First, a test to confirm that we can emulate ADS-B, GPS, and INS sensor data corruption, leading to recovery using backup flight (lidar, EO/IR) or ground (radar, EO/IR) data to safely land an ALTA6 or other test UAS. Second, a series of Sense-and-Avoid (SAA) experiments between our test UAS and a tethered aerial obstacle. In the future, we will use this experience with fail-safe, fail-secure methods and software to further test more advanced scenarios between multiple UAS. The network of Drone Net instruments in a local area as well as regional and more global cloud-based networks will allow for heterogeneous information fusion and algorithm development for multi-sensor drone detection, classification, and identification with more accuracy than a single database or sensor system. The latent power of the Drone Net project is in its open-design ground and flight sensor network with data sharing capability to improve data mining and machine learning over time for analysis and security applications. More concrete applications for Drone Net include UTM integration with ATC and UAM, but also airspace safety and security for campus and public venues in general. Herein, we will present our experimental design and current test data from Embry-Riddle Aeronautical University in collaboration with University of Colorado Boulder toward completing the open specification for ground and flight instruments. We would additionally like to invite others to participate in growing the network and the data available for UTM, UAM, and GA shared airspace research.

This work presents a risk assessment methodology, preliminary proposed in [1], which is the fusion of the absolute and the relative risk assessment methods adopted by the International Civil Aviation Organization. The proposed methodology uses the Fluid Stochastic Petri Net (FSPN) as modeling formalism, and compares the safety metrics estimated from the simulation of both the proposed and the legacy system models. It was applied to assess the safety properties of a new air traffic surveillance concept, named automatic dependent surveillance - broadcasting (ADS-B). As conclusions, the proposed methodology assured to assess the safety properties of systems based on the current safety critical system paradigm - especially concerning the air transportation system. Besides, the FSPN formalism provided important modeling capabilities and discrete event simulation allowing estimating the desired safety metrics. Finally, the ADS-B (proposed system) has significantly reduced the risks of separation losses between aircrafts if compared to the usual surveillance radar systems (legacy system) in air traffic control (ATC) environment.

This paper designs, simulates, and tests a potential Automatic Dependent Surveillance-Broadcast (ADS-B) space-oriented message set to improve situational awareness of commercial space vehicles inside the National Airspace System (NAS), and to minimize their impacts and potential hazards on the NAS. ADS-B is considered as the solution to integrate the future commercial space transportation system with the air transportation system. To accommodate future space flight operations in the NAS, a potential ADS-B space-oriented message set is proposed to be exclusively transmitted from space vehicles to other traffic and air traffic controllers. New data fields are defined in the message set to cover a space vehicle's entire flight profile. The formats of these new data fields are demonstrated in details. A simulation is created containing space vehicle and aircraft trajectories to test the functionality of the ADS-B space-oriented message set. The message set is encoded at the space vehicle site, transmitted from space vehicle to aircraft via the Universal Access Transceiver (UAT) datalink, and decoded at the aircraft site. The simulation eventually reaches a conflict scenario. By using the Closest Point of Approach (CPA) algorithm, the aircraft analyzes its own state vector and the space vehicle's state vector decoded from ADS-B messages to perform conflict detection. Sensitivity studies are conducted based on the CPA algorithm concentrating on three ADS-B system parameters, which are message update rate, data latency, and state vector accuracy.

Energy efficiency, noise and emissions footprint reduction are major “green” performance targets of next-generation air transportation systems. Automatic Dependent Surveillance Broadcast (ADS-B) is an advanced “cyber-physical” concept that can help meet such targets by enabling highly accurate air traffic surveillance. However, beneficial, confident application of ADS-B requires a foundational understanding of vulnerabilities and mitigation requirements. This paper focuses on the assessment and mitigation of threats from unauthorized access and unanticipated disruption of ADS-B communications. We present a solution to protect message integrity in ADS-B IN based airborne surveillance, discuss the accuracy and robustness of the solution in the presence of spoofed or compromised nodes and intentional jamming. To study effects of “intelligent jamming” strategies on ADS-B, visualize and analyze system-wide impact, we propose a security simulation tool concept and design.

Adapting a Human – Automation Trust Scale to an Air Traffic Management Environment

The US Federal Aviation Administration is proposing an upgrade to air transportation that will fundamentally overhaul the current, aging system. A key component, the automatic dependent surveillance broadcast (ADS-B) system, will enhance air traffic monitoring and control by requiring aircraft to continually broadcast position, identity and velocity via unencrypted data links to ground stations. Although ADS-B may enhance air traffic safety and support the increase in traffic demands, open broadcast of clear aircraft data points raise serious security concerns. The ability to encrypt ADS-B message transactions would afford protection to ensure that the confidentiality of aircraft data is not compromised. The implementation of an encryption framework for a large, distributed and dynamic system, however, is nontrivial. This paper examines encryption schemes and highlights challenges associated with implementing confidentiality security protections for the ADS-B environment.