Ricerc@Sapienza

This paper deals with the detection of small unmanned air vehicles (UAVs) and drones in high-density target scenarios such as airport terminal areas. In fact, in such conditions, strong reflections by high radar cross section (RCS) targets are likely to prevent the detection of very weak target echoes. In this work, we aim at overcoming this issue by taking advantage of long coherent processing intervals (CPIs) and by implementing a CLEAN-like multistage algorithm to remove the strongest target contributions.

The capability of WiFi-based passive radar to detect, track and profile human targets in both indoor and outdoor environment has been widely demonstrated. This paper investigates the impact of the Beacon Interval (BI) on the passive radar performance. The results of a dedicated acquisition campaign show that both the detection capability and the localization accuracy progressively degrade as the BI increases due to both the reduction of the received beacons and to the intrinsic undersampling of the target motion. Limit values are suggested for practical applications.

In this paper two approaches are considered for human targets localization based on the WiFi signals: the device emission-based localization and the passive radar. Localization performance and characteristics of the two localization techniques are analyzed and compared, aiming at their joint exploitation inside sensor fusion systems. The former combines the Angle of Arrival (AoA) and the Time Difference of Arrival (TDoA) measures of the device transmissions to achieve the target position, while the latter exploits the AoA and the bistatic range measures of the target echoes.

This paper focuses on the exploitation of a single node Forward Scatter Radar configuration for the estimation of the kinematic parameters of targets following a linear trajectory. Accordingly, the target signature extracted from a square law detector followed by a DC removal filter is exploited. A four step processing technique is proposed for the estimation of the main target parameters encoding Doppler rate and derivative of the Doppler rate that are exploited for the extraction of the target motion parameters.

This paper focuses on a passive radar system based on Global Navigation Satellite Systems for maritime surveillance. While in the past the capability of this technology to detect ship targets at sea was proved, despite the low EIRP level of the GNSS, the objective of this paper is investigating the potential of the system to extract information concerning the detected target characteristics.

The focus of this paper is on multi-transmitter GNSS passive radar for maritime surveillance. Particularly, working in the range-Doppler domain, the possibility to integrate over long time intervals (required to counteract restricted power budget provided by navigation satellites) the returns from a moving target illuminated by multiple GNSS transmitters is experimentally demonstrated.

This paper is a first introduction to the concept of using global navigation satellite systems (GNSS) as illuminators of opportunity in a passive bistatic real-time radar system for maritime target indication applications. An overview of the system concept and the signal processing algorithms for moving target indication is provided.

This work investigates the potentialities of DVB-S based passive ISAR for maritime surveillance applications. Specifically, in order to characterize the bound on the achievable performance, a knowledge based approach is adopted: Assuming known the target motion, the image is focused in both the range/Doppler domain and the x-y plane via backprojection. The approach is applied to experimental data acquired during a field trial by exploiting an experimental system developed at Fraunhofer FHR.

This work presents an analysis of passive inverse synthetic aperture radar images obtained exploiting simultaneously digital video broadcasting-Terrestrial (DVB-T) and digital video broadcasting-satellite (DVB-S) as illuminators of opportunity (IOs) over a cooperative maritime target with known motion. The combined exploitation of these two IOs is extremely appealing for passive imaging purposes, given their complementary characteristics.

This work discusses methods and experimental results on passive radar detection of moving ships using navigation satellites as transmitters of opportunity. The reported study highlights as the adoption of proper strategies combining target motion compensation and track-before-detect methods to achieve long time integration can be fruitfully exploited in GNSS-based passive radar for the detection of maritime targets.