Decentralized approach for translational motion estimation with multistatic inverse synthetic aperture radar systems

This paper addresses the estimation of the target translational motion by using a multistatic Inverse Synthetic Aperture Radar (ISAR) system composed of an active radar sensor and multiple receiving-only devices. Particularly, a two-step decentralized technique is derived: the first step estimates specific signal parameters (i.e., Doppler frequency and Doppler rate) at the single-sensor level, while the second step exploits these estimated parameters to derive the target velocity and acceleration components. Specifically, the second step is organized in two stages: the former is for velocity estimation, while the latter is devoted to velocity estimation refinement if a constant velocity model motion can be regarded as acceptable, or to acceleration estimation if a constant velocity assumption does not apply. A proper decision criterion to select between the two motion models is also provided. A closed-form theoretical performance analysis is provided for the overall technique, which is then used to assess the achievable performance under different distributions of the radar sensors. Additionally, a comparison with a state-of-the-art centralized approach has been carried out considering computational burden and robustness. Finally, results obtained against experimental multisensory data are shown confirming the effectiveness of the proposed technique and supporting its practical application

Translational velocity estimation by means of bistatic isar techniques

In the last years significant effort has been dedicated to prove that increased information and/or better performance can be retrieved in radar and radar imaging using a network of cooperating sensors. In this paper, data acquired by two Inverse Synthetic Aperture Radar sensors observing a target from different points of view in the long range surveillance operative case is exploited to estimate both radial and cross-radial components of a target's translational motion. Simulated objective functions prove the feasibility of the proposed techniques, confirmed by the analysis of the results of their application against real data acquired by the Radar Sensor Network installed at the NATO Centre for Maritime Research and Experimentation. © 2015 IEEE