Efficient Algorithm to Calculate a Time-Domain Echo Signal from Moving Targets Based on Physical Optics and the Application to an Autonomous Driving Simulation

An automotive radar simulator is proposed that can consider a dynamic driving scenario. The impulse response is computed based on the distance between the radar and the mesh position and the radar equation. The first-order physical optics technique is used to calculate the backscattering by the meshes, which can efficiently consider the shape of the target; however, because the radar operating frequency is very high, the required amount of mesh for discretization is large. Hence, the calculation of the time-domain echo signal requires considerable computational time. To reduce this numerical complexity, a new scheme is proposed to accurately approximate the time-domain baseband signal generated by the large number of meshes. The radar adopts the frequency modulated continuous waveform. Range-Doppler processing is used to estimate the range and relative velocity of the targets based on which simulation results are numerically verified for a driving scenario.

Blind signal separation based on widely linear complex autoregressive process of order one

In this paper, the blind signal separation problem of complex baseband signal is addressed. A widely linear complex autoregressive process of order one is employed to represent the temporal structure of complex sources. We formulate a new contrast function by a convex combination of generalized autocorrelations and the statistics of the innovation. And the proposed contrast function is optimized by gradient method. Simulation results show that the proposed algorithm is better than the comparison algorithm in convergence speed and convergence accuracy.

A Spatial-Temporal Approach Based on Antenna Array for GNSS Anti-Spoofing

The presence of spoofing signals poses a significant threat to global navigation satellite system (GNSS)-based positioning applications, as it could cause a malfunction of the positioning service. Therefore, the main objective of this paper is to present a spatial-temporal technique that enables GNSS receivers to reliably detect and suppress spoofing. The technique, which is based on antenna array, can be divided into two consecutive stages. In the first stage, an improved eigen space spectrum is constructed for direction of arrival (DOA) estimation. To this end, a signal preprocessing scheme is provided to solve the signal model mismatch in the DOA estimation for navigation signals. In the second stage, we design an optimization problem for power estimation with the estimated DOA as support information. After that, the spoofing detection is achieved by combining power comparison and cross-correlation monitoring. Finally, we enhance the genuine signals by beamforming while the subspace oblique projection is used to suppress spoofing. The proposed technique does not depend on external hardware and can be readily implemented on raw digital baseband signal before the despreading of GNSS receivers. Crucially, the low-power spoofing attack and multipath can be distinguished and mitigated by this technique. The estimated DOA and power are both beneficial for subsequent spoofing localization. The simulation results demonstrate the effectiveness of our method.

An FPGA Scalable Software-Defined Radio Platform for UAS Communications Research

In the framework of modern Unmanned Aerial System (UAS) ground-board communications, a data-link system should provide with the following features [1]: multiband and adaptive modulations for responding to channel conditions changes and multi-standard interoperability, interferences resilience with a secure physical layer, incorporation of an air-to-air link complementary to the classical air-to-ground links. Varying the available communication functions to provide the above features without the need to substitute on-board components is a desired target. For this purpose, a Field Programmable Gate Aray (FPGA) scalable Software Defined Radio hardware Platform (SDRP) and its control and baseband signal processing architecture have been developed. The platform is composed by means of three boards which provide respectively the power supply, an FPGA based processing core and the radio frequency front-end. The control and baseband signal processing architecture, implemented on the FPGA, is designed with an application-independent section, working as a base reference design, and a reconfigurable section that implements communication functions and algorithms. The overall platform, at the board and FPGA architecture level, has been designed considering scalability and modularity as key features. Thanks to this platform a data-link which responds to the above target can be easily implemented. As a case study a reconfigurable data-link between a UAS and a Ground Control Station (GCS), designed to establish reliable communication in all the phases of a flight (parking, taxiing, taking off, cruising and landing), is presented.