Advanced signal processing tools for ballistic missile defence and space situational awareness

The research presented in this Thesis deals with signal processing algorithms for the classification of sensitive targets for defence applications and with novel solutions for the detection of space objects. These novel tools include classification algorithms for Ballistic Targets (BTs) from both micro-Doppler (mD) and High Resolution Range Profiles (HRRPs) of a target, and a space-borne Passive Bistatic Radar (PBR) designed for exploiting the advantages guaranteed by the Forward Scattering (FS) configuration for the detection and identification of targets orbiting around the Earth.;Nowadays the challenge of the identification of Ballistic Missile (BM) warheads in a cloud of decoys and debris is essential in order to optimize the use of ammunition resources. In this Thesis, two different and efficient robust frameworks are presented. Both the frameworks exploit in different fashions the effect in the radar return of micro-motions exhibited by the target during its flight.;The first algorithm analyses the radar echo from the target in the time-frequency domain, with the aim to extract the mD information. Specifically, the Cadence Velocity Diagram (CVD) from the received signal is evaluated as mD profile of the target, where the mD components composing the radar echo and their repetition rates are shown.;Different feature extraction approaches are proposed based on the estimation of statistical indices from the 1-Dimensional (1D) Averaged CVD (ACVD), on the evaluation of pseudo-Zerike (pZ) and Krawtchouk (Kr) image moments and on the use of 2-Dimensional (2D) Gabor filter, considering the CVD as 2D image. The reliability of the proposed feature extraction approaches is tested on both simulated and real data, demonstrating the adaptivity of the framework to different radar scenarios and to different amount of available resources.;The real data are realized in laboratory, conducting an experiment for simulating the mD signature of a BT by using scaled replicas of the targets, a robotic manipulator for the micro-motions simulation and a Continuous Waveform (CW) radar for the radar measurements.;The second algorithm is based on the computation of the Inverse Radon Transform (IRT) of the target signature, represented by a HRRP frame acquired within an entire period of the main rotating motion of the target, which are precession for warheads and tumbling for decoys. Following, pZ moments of the resulting transformation are evaluated as final feature vector for the classifier. The features guarantee robustness against the target dimensions and the initial phase and the angular velocity of its motion.;The classification results on simulated data are shown for different polarization of the ElectroMagnetic (EM) radar waveform and for various operational conditions, confirming the the validity of the algorithm.The knowledge of space debris population is of fundamental importance for the safety of both the existing and new space missions. In this Thesis, a low budget solution to detect and possibly track space debris and satellites in Low Earth Orbit (LEO) is proposed.;The concept consists in a space-borne PBR installed on a CubeSaT flying at low altitude and detecting the occultations of radio signals coming from existing satellites flying at higher altitudes. The feasibility of such a PBR system is conducted, with key performance such as metrics the minimumsize of detectable objects, taking into account 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. Finally, the designed system can represent a possible solution to the the demand for Ballistic Missile Defence (BMD) systems able to provide early warning and classification and its potential has been assessed also for this purpose.The research presented in this Thesis deals with signal processing algorithms for the classification of sensitive targets for defence applications and with novel solutions for the detection of space objects. These novel tools include classification algorithms for Ballistic Targets (BTs) from both micro-Doppler (mD) and High Resolution Range Profiles (HRRPs) of a target, and a space-borne Passive Bistatic Radar (PBR) designed for exploiting the advantages guaranteed by the Forward Scattering (FS) configuration for the detection and identification of targets orbiting around the Earth.;Nowadays the challenge of the identification of Ballistic Missile (BM) warheads in a cloud of decoys and debris is essential in order to optimize the use of ammunition resources. In this Thesis, two different and efficient robust frameworks are presented. Both the frameworks exploit in different fashions the effect in the radar return of micro-motions exhibited by the target during its flight.;The first algorithm analyses the radar echo from the target in the time-frequency domain, with the aim to extract the mD information. Specifically, the Cadence Velocity Diagram (CVD) from the received signal is evaluated as mD profile of the target, where the mD components composing the radar echo and their repetition rates are shown.;Different feature extraction approaches are proposed based on the estimation of statistical indices from the 1-Dimensional (1D) Averaged CVD (ACVD), on the evaluation of pseudo-Zerike (pZ) and Krawtchouk (Kr) image moments and on the use of 2-Dimensional (2D) Gabor filter, considering the CVD as 2D image. The reliability of the proposed feature extraction approaches is tested on both simulated and real data, demonstrating the adaptivity of the framework to different radar scenarios and to different amount of available resources.;The real data are realized in laboratory, conducting an experiment for simulating the mD signature of a BT by using scaled replicas of the targets, a robotic manipulator for the micro-motions simulation and a Continuous Waveform (CW) radar for the radar measurements.;The second algorithm is based on the computation of the Inverse Radon Transform (IRT) of the target signature, represented by a HRRP frame acquired within an entire period of the main rotating motion of the target, which are precession for warheads and tumbling for decoys. Following, pZ moments of the resulting transformation are evaluated as final feature vector for the classifier. The features guarantee robustness against the target dimensions and the initial phase and the angular velocity of its motion.;The classification results on simulated data are shown for different polarization of the ElectroMagnetic (EM) radar waveform and for various operational conditions, confirming the the validity of the algorithm.The knowledge of space debris population is of fundamental importance for the safety of both the existing and new space missions. In this Thesis, a low budget solution to detect and possibly track space debris and satellites in Low Earth Orbit (LEO) is proposed.;The concept consists in a space-borne PBR installed on a CubeSaT flying at low altitude and detecting the occultations of radio signals coming from existing satellites flying at higher altitudes. The feasibility of such a PBR system is conducted, with key performance such as metrics the minimumsize of detectable objects, taking into account 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. Finally, the designed system can represent a possible solution to the the demand for Ballistic Missile Defence (BMD) systems able to provide early warning and classification and its potential has been assessed also for this purpose

Micro-doppler classification of ballistic threats using krawtchouk moments

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

CubeSat-based passive bistatic radar for space situational awareness : a feasibility study

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

Performance analysis of co-located and distributed MIMO radar for micro-doppler classification

Over the past few years, the use of Multiple Input Multiple Output (MIMO) radar has gained increased attention as a way to mitigate the degredation of micro-Doppler classification performance incurred when the aspect angle approaches 90 degrees. In this work, the efficacy of co-located MIMO radar is compared with that of distributed MIMO. The performance anaylsis is accomplished for three different classification problems: 1) discrimination of a walking group of people from a running group of people; 2) identification of individual human activities, and 3) classification of different types of walking. In the co-located configuration each radar is placed side by side so as to form a line. In the distributed configuration, the radar positions are separated to observe the subjects from different angles. Starting from the cadence velocity diagram (CVD), the Pseudo-Zernike moments based features are extracted because of their robustness with respect to unwanted scalar and angular dependencies. Two different approaches to integrate the features obtained from multi-aspect data are compared: concatenation and principal component analysis (PCA). Results show that a distributed MIMO configuration and use of PCA to fuse multiperspective features yields higher classification performance as compared to a co-located configuration or feature vector concatenation

Micro-Doppler based recognition of ballistic targets using 2D gabor filters

The capability to recognize ballistic threats, is a critical topic due to the increasing effectiveness of resultant objects 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 the micro-Doppler signatures in conjunction with the 2-Dimensional Gabor filter is presented for this problem. The effectiveness of the proposed approach is demonstrated through the use of real data

Novel approach for ballistic targets classification from HRRP frame

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

Fractional fourier transform based waveform for a joint radar-communication system

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

On model, algorithms and experiment for micro-doppler based recognition of ballistic targets

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 defence system can intercept the missile is very short with respect to target velocities, it is fundamental to minimise the number of shoots per kill. For this reason a reliable technique to classify warheads and confusing objects is required. In the efficient warhead classification system presented in this paper a model and a robust framework is developed, which incorporates different microDoppler based classification techniques. The reliability of the proposed framework is tested on both simulated and real dat

Waveform design for communicating radar systems using fractional Fourier transform

A novel waveform design technique for enabling a communication channel within a pulse radar is presented. The proposed waveform is composed of quasi-orthogonal chirp sub-carriers generated by means of the Fractional Fourier Transform (FrFT), with the aim of preserving the radar performance of a typical Linear Frequency Modulated (LFM) pulse while embedding data to be sent to a cooperative system. Waveform generation and demodulation are described, together with techniques aimed at optimising the design parameters and mitigating the Inter-Carrier Interference (ICI) caused by the quasi-orthogonality of the chirp sub-carriers. The proposed FrFT based communicating-radar (CoRadar) waveform design is compared with Orthogonal Frequency Division Multiplexing (OFDM) based CoRadar with respect to both radar and communication operations. Radar performance is evaluated through examination of the Ambiguity Function (AF) and by assessing the performance of a standard square law detector. Communication performance is shown in terms of Bit Error Ratio (BER) for different channel conditions. Results demonstrate that the proposed FrFT waveform presents performance close to a LFM pulse in terms of probability of detection and probability of false alarm, in exchange for slightly worse range and Doppler resolution. Furthermore, it is shown to maintain comparable communication performance with respect to the OFDM waveform. Finally, a hardware implementation is described that demonstrates the simultaneous radar and communication capabilities of the proposed system

Design of f-SCAN Acquisition Mode for Synthetic Aperture Radar

This paper presents the design and processing of the SAR acquisition technique named frequency scanning (f-SCAN), aimed to obtain high sensitivity to targets with low backscattering and to improve the signal-to-noise ratio (SNR) in wide-swath systems. The f-SCAN is an interesting alternative to the scanning on receive method (SCORE), which needs multiple phase centres achieved using the digital beam forming (DBF) technique. f-SCAN requires less hardware complexity than SCORE; at the same time, it improves the sidelobes and ambiguities’ suppression. The elements used in f-SCAN to generate the pencil beam are the true time delay lines (TTDLs) and the phase shifters (PSs). The general methodology to design an f-SCAN spaceborne SAR high-resolution wide-swath (HRWS) system is introduced; emphasis is put on the mathematical definition of the timing parameters and on a novel method of using TTDLs to achieve the full spanning of wide swaths. The processing of f-SCAN data is also considered: we introduce a novel algorithm to limit the data volume and to guarantee an almost invariant slant range impulse response function (IRF) by removing spectral distortions. Eventually, new definitions, specific for f-SCAN, of the well-known SAR performance parameters, are provided. Simulation results and performances are presented. The advantages and disadvantages with respect to SCORE are discussed using the design of a real case system