In the next generation modernization plan, the automatic dependent surveillance-broadcast (ADS-B) system plays a pivotal role. However, the ADS-B’s low level of security and its vulnerabilities have raised valid concerns. The main objectives of this paper are to highlight the limitations of legacy ADS-B systems and to assess the feasibility of using Format-preserving (F), Feistel-based encryption (F), with multiple implementation variances (X) (FFX) algorithms, for enhancing ADS-B’s security. The offered solution is implemented in a standard software-defined radio (SDR) ADS-B to be utilized in real-time applications. Furthermore, a new proposed blockchain scheme is used as a secured database to manage the cipher key. The metric of message entropy is used to assess an algorithm’s ability to confuse and diffuse predictable ADS-B messages; correlation and serial correlation of plain data and cipher data are deployed to evaluate the proposed method’s security level. The authors provide both MATLAB simulations and flight test outcomes to demonstrate the feasibility of this approach. Based on our security analysis, ADS-B information can be kept confidential through our scheme. The performance evaluation results reveal that the proposed scheme is achievable, compatible, and efficient for the avionics industry.

This paper provides research on the enhanced NextGen ADS-B reception method and its performance in laboratory and flight tests. It sheds the light on end-to-end reception techniques to comply with key requirements. ADS-B has emerged as among the most intriguing avionics for both researchers and companies since the launch of NextGen in 2009. ADS-B provides authorities with a mechanism for use in continuously monitoring the position and track of an airplane using periodic and independent broadcast messages that transmit Global Navigation Satellite System (GNSS) position information. The enhanced pulse detection technique is used to detect and validated preamble pulses. Besides the utilization of multiple amplitude samples technique not only improve bit and confidence declaration accuracy but also make it capable of deploying error detection/correction algorithms which are two aspects of enhanced Extended Squitter reception. In addition, applying a slow attack automatic gain control (AGC) algorithm improves system sensitivity and performance. The implementation is done in MATLAB Simulink and C++. Software Defined Radio (SDR) module, BladeRF, is used programable platform for the communication system. Subsequently, the lab experimental and flight test results show that when applying these strategies in a real environment, significant performance is achievable.

This study introduces a reconfigurable and agile RF front-end (RFFE) architecture that significantly enhances the performance of software-defined radios (SDRs) by seamlessly adjusting to varying signal requirements, frequencies, and protocols. This flexibility greatly enhances spectrum utilization, signal integrity, and overall system efficiency—critical factors in aviation, where reliable communication, navigation, and surveillance systems are vital for safety. A versatile RF front-end is thus indispensable, enhancing connectivity and safety standards. We explore the integration of this flexible RF front-end in SDRs, focusing on the detailed design of essential components, such as receivers, transmitters, RF switches, combiners, and splitters, and their corresponding RF pathways. Comprehensive performance evaluations confirm the architecture’s reliability and functionality, including an extensive analysis of receiver gain, linearity, and two-tone test results. These assessments validate the architecture’s suitability for aviation radios and address considerations of size, weight, and power-cost (SWaP-C), demonstrating significant gains in operational efficiency and cost-effectiveness. The introduction of the new RF front-end on a single SDR board not only substantially reduces size and weight but also adds up to 18 dB gain to the received signal. It also allows for a high level of design flexibility, enabling seamless software transitions between different radios and the capacity to manage three times more radios with the same hardware, thereby significantly boosting the system’s ability to handle multiple radio channels efficiently.

This paper presents an end-to-end, CPU/GPU-based real-time framework for code-independent static positioning using signals of opportunity (SoOP) from IridiumNext and Orbcomm. The proposed architecture combines low-cost SDR signal acquisition with Doppler feature extraction, satellite identification, and fast orbital dynamics prediction, followed by parallel robust/nonlinear estimation and fusion. To mitigate the problems of outliers and non-ideal Doppler conditions, a Huber nonlinear least-squares stage is used for robust initialization, while EKF and UKF provide sequential refinement. To accommodate variations in measurement uncertainty and potentially multimodal state distributions, an interacting multiple-model unscented Kalman filter (IMM-UKF) and a Gaussian sum filter (GSF) are implemented, respectively. These five estimators operate concurrently, and their outputs are fused using a heatmap-based accumulation with anisotropic rotated Gaussian kernels and adaptive search-range control, enabling stable real-time operation under intermittent satellite availability. In a 30-minute outdoor static experiment (15° elevation mask, cloudy conditions, −8°C), five IridiumNext and four Orbcomm satellites were detected (of 13 and seven that were predicted to be visible, respectively). Post-processing analysis revealed approximately Gaussian but non-zero-mean Doppler residuals, indicating effective frequency offsets potentially associated with receiver and transmitter oscillator uncertainties. An investigation of zero-Doppler crossing (ZDC) events highlighted their potential for coarse frequency-bias calibration. With a processing window of δt=0.01s, the system achieved a minimum 2D positioning error of ~1m and a final 2D error of ~9.91m at the end of the test, thus demonstrating the feasibility of real-time, code-independent SoOP static positioning with meter-level performance under real-world conditions.