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RaSS (Radar and Surveillance Systems) National Laboratory, CNIT (National Inter-University Consortium for Telecommunications), 56124 Pisa, Italy
Interests: passive radar systems; HF-OTH radars; array processing; neural network applications in target classification; synthetic range profile reconstruction; weather radars signal processing; sea surface fractal modeling for environmental monitoring applications; space debris detection and design of fully digital radar based on photonic technologies
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Special Issue Information

Dear Colleagues,

This Special Issue aims to gather the latest research results in the area of radar technology using active and/or passive radar imaging techniques in different applications, both military and civilian.

The rapid growth of the technology, the availability of enhanced computational resources, the development of new signal processing techniques, have made the implementation of radar imaging techniques more effective and also feasible on passive radar systems. This class of radars have gained a renewed interest from the worldwide scientific community thanks to their advantages over active radar systems (e.g., covertness, no e.m. emission, low vulnerability to electronic countermeasure, counter-stealth advantage) and to the advances in the technology which have made the realization of real time systems feasible and affordable.

This Special Issue aims at collecting papers on recent advancements in the area of active and/or passive radar imaging covering both passive synthetic-aperture radar (SAR) and inverse synthetic aperture radar (P-ISAR) imaging.

Dr. Amerigo Capria
Guest Editor

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Keywords

PBR
bistatic radar
passive radar
radar imaging
SAR
P-ISAR
ISAR
radar target recognition
synthetic aperture radar
inverse synthetic aperture radar
passive multistatic SAR

Published Papers (2 papers)

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Research

Open AccessArticle

An Improved Ground Moving Target Parameter Estimation and Imaging Method for Multichannel High Resolution SAR

and

Appl. Sci. 2022, 12(10), 4934; https://doi.org/10.3390/app12104934 - 13 May 2022

Viewed by 621

Abstract

With increasing demands from both military and civilian applications, ground moving-target imaging is becoming one of the important research topics for high-resolution SAR systems. However, the existing moving-target imaging methods are not suitable for high-resolution SAR because of their low parameter estimation accuracy and high computational complexity. To solve the problem, an improved ground moving-target parameter estimation and imaging method is proposed. First, the third-order phase model of the uniformly accelerated target signal is constructed, and the Hough transform and the second-order Keystone transform (SOKT) are used to correct the range cell migration into one range cell to achieve target coherent accumulation. Secondly, a delayed cross-correlation function (DCCF) is constructed to reduce the order of the range migration phase response in the slow time domain, and the coupling degree between the cross-correlation peak position and the range migration is reduced, so that the obtained DCCF has a higher gain, which ensures the accuracy of parameter estimation. Parameter estimation is simplified to peak detection by the Shift-And-Correlation (SAC) algorithm and two-dimensional Fourier transform (2D-FFT), avoiding parameter search. Compared with the existing methods, the proposed method has better focusing effect and lower computational complexity. Finally, simulation and measured data are given to verify the effectiveness of the proposed method. Full article

(This article belongs to the Special Issue Recent Advances in Radar Imaging)

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Open AccessArticle

Dynamic Programming Ring for Point Target Detection

and

Appl. Sci. 2022, 12(3), 1151; https://doi.org/10.3390/app12031151 - 22 Jan 2022

Cited by 1 | Viewed by 867

Abstract

To improve the detection efficiency of a long-distance dim point target based on dynamic programming (DP), this paper proposes a multi-frame target detection algorithm based on a merit function filtering DP ring (MFF-DPR). First, to reduce the influence of noise on the pixel state estimation results, a second-order DP named the MFF-DP is proposed. The current states of pixels on an image plane are estimated by maximizing the addition of the merit functions of the previous two frames and the observation data of the current frame. In addition, to suppress the diffusion of the merit function, the sequential and reverse observation data are connected in a head-to-tail manner to form a ring structure. The MFF-DP is applied to the ring structure, and the merit function of the MFF-DPR is obtained by averaging the merit functions of the sequential and reverse MFF-DPs. Finally, the target trajectory is obtained by correlating the extreme points of the merit functions of the MFF-DPR. The simulation and analysis results show that by merely adding a ring structure, the detection probability of the traditional DP can be improved by up to 40% when detecting point targets under the SNR of 1.8. The point target detection algorithm based on the MFF-DPR can achieve significantly better performance in point target detection compared with the traditional DPs with or without a ring structure. The proposed algorithm is suitable for radars and infrared point target detection systems. Full article

(This article belongs to the Special Issue Recent Advances in Radar Imaging)

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