The ability to discriminate between ballistic missile warheads and confusing objects is an important topic from different points of view. In particular, the high cost of the interceptors with respect to tactical missiles may lead to an ammunition problem. Moreover, since the time interval in which the defense system can intercept the missile is very short with respect to target velocities, it is fundamental to Manuscript

Abstract-The increasing demand of spectrum resources and the need to keep the size, weight and power consumption of modern radar as low as possible, has led to the development of solutions like joint radar-communication systems. In this paper a novel Fractional Fourier Transform (FrFT) based multiplexing scheme is presented as joint radar-communication technique. The FrFT is used to embed data into chirp sub-carriers with different time-frequency rates. Some optimisation procedures are also proposed, with the objective of improving the bandwidth occupancy and the bit rate and/or Bit Error Ratio (BER). The generated waveform is demonstrated to have a good rejection to distortions introduced by the channel, leading to low BER, while keeping good radar characteristics compared to a widely used Linear Frequency Modulated (LFM) pulse with same duration and bandwidth.

No abstract

Nowadays the identification of ballistic missile warheads in a cloud of decoys and debris is essential for defence systems in order to optimize the use of ammunition resources, avoiding to run out of all the available interceptors in vain. This paper introduces a novel solution for the classification of ballistic targets based on the computation of the inverse Radon transform of the target signatures, represented by a high resolution range profile frame acquired within an entire period of the main rotation of the target. Namely, the precession for warheads and the tumbling for decoys are taken into account. Following, the pseudo-Zernike moments of the resulting transformation are evaluated as the final feature vector for the classifier. The extracted features guarantee robustness against target's dimensions and rotation velocity, and the initial phase of the target's motion. The classification results on simulated data are shown for different polarizations of the electromagnetic radar waveform and for various operational conditions, confirming the validity of the algorithm.

This paper proposes a low budget solution to detect and possibly track space debris and satellites in Low Earth Orbit. The concept consists of a space-borne radar installed on a cubeSat flying at low altitude and detecting the occultations of radio signals coming from existing satellites flying at higher altitudes. The paper investigates the feasibility and performance of such a passive bistatic radar system. Key performance metrics considered in this paper are: the minimum size of detectable objects, considering visibility and frequency constraints on existing radio sources, the receiver size, and the compatibility with current cubeSat's technology. Different illuminator types and receiver altitudes are considered under the assumption that all illuminators and receivers are on circular orbits.

The capability to recognize ballistic threats, is a critical topic due to the increasing effectiveness of countermeasures and to economical constraints. In particular the ability to distinguish between warheads and decoys is crucial in order to mitigate the number of shots per hit and to maximize the ammunition capabilities. For this reason a reliable technique to classify warheads and decoys is required. In this paper the use of micro-Doppler signatures in conjunction with the 2-Dimensional Gabor transform is presented for this problem. The effectiveness of the proposed approach is demonstrated through the use of real data.

Nowadays the challenge of the identification of Ballistic Missile (BM) warheads in a cloud of decoys and debris is essential for the defence system in order to optimize the use of ammunition resources avoiding to run out of all the available interceptors in vain. In this paper a novel approach for the classification of ballistic threats from the High Resolution Range Profile (HRRP) frame is presented. The algorithm is based on the computation of the inverse Radon Transform (IRT) of the HRRP frame as target signature, and on the evaluation of pseudo-Zernike moments, as final feature vector. Firstly, the algorithm is presented emphasizing the characteristics of the HRRP frame due to target micro-motions. Then, the classification results on simulated data are shown for various operational conditions.

This version is available at https://strathprints.strath.ac.uk/56501/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. Micro-Doppler Classification of Ballistic Threats Using Krawtchouk MomentsAdriano Rosario Persico * , Carmine Clemente * , Luca Pallotta † , Antonio De Maio ‡ and John Soraghan * * University of Strathclyde, CESIP, EEE, 204, George Street, G1 1XW, Glasgow, UK E-mail: adriano.persico, carmine.clemente, j.soraghan-@strath.ac.uk † CNIT, viale G.P. Usberti, n. 181/A -43124 Parma, c/o udr Università "Federico II", via Claudio 21, I-80125 Napoli, Italy. E-mail: luca.pallotta@unina.it. ‡ Università degli Studi di Napoli "Federico II", Dipartimento di Ingegneria Elettrica e delle Tecnologie dellInformazione, Via Claudio 21, I-80125 Napoli, Italy. E-mail: ademaio@unina.it.Abstract-The challenge of ballistic missiles classification is getting greater importance in last years. In fact, since the antimissile defence systems have generally a limited number of interceptors, it is important to distinguish between warheads and confusing objects that the missile releases during its flight, in order to maximize the interception success ratio. For this aim, a novel micro-Doppler based classification technique is presented in this paper characterized by the employment of Krawtchouk moments. Since the evaluation of the latter requires a low computational time, the proposed approach is suitable for real time applications. Finally, a comparison with the 2-dimensional Gabor filter based approach is described by testing both the techniques on real radar data.