Investigations on OFDM Signal for Range Ambiguity Suppression in SAR Configuration

International audienceThis paper presents an opportunity to cancel range ambiguities in synthetic aperture radar (SAR) configuration. One of the limitations of SAR systems is the range ambiguity phenomenon that appears with long delayed echoes. The reflected signal corresponding to one pulse is detected when the radar has already transmitted the next pulse. Thus, this signal is considered as an echo from the next pulse. This paper investigates the opportunity of coding the transmitted pulses using an orthogonal frequency-division multiplexing pulse. The results show that coded-OFDM signals outperform conventional chirp signal and make it possible to relax constraints placed upon the pulse repetition frequency

Advanced signal processing solutions for ATR and spectrum sharing in distributed radar systems

Previously held under moratorium from 11 September 2017 until 16 February 2022This Thesis presents advanced signal processing solutions for Automatic Target Recognition (ATR) operations and for spectrum sharing in distributed radar systems. Two Synthetic Aperture Radar (SAR) ATR algorithms are described for full- and single-polarimetric images, and tested on the GOTCHA and the MSTAR datasets. The first one exploits the Krogager polarimetric decomposition in order to enhance peculiar scattering mechanisms from manmade targets, used in combination with the pseudo-Zernike image moments. The second algorithm employs the Krawtchouk image moments, that, being discrete defined, provide better representations of targets’ details. The proposed image moments based framework can be extended to the availability of several images from multiple sensors through the implementation of a simple fusion rule. A model-based micro-Doppler algorithm is developed for the identification of helicopters. The approach relies on the proposed sparse representation of the signal scattered from the helicopter’s rotor and received by the radar. Such a sparse representation is obtained through the application of a greedy sparse recovery framework, with the goal of estimating the number, the length and the rotation speed of the blades, parameters that are peculiar for each helicopter’s model. The algorithm is extended to deal with the identification of multiple helicopters flying in formation that cannot be resolved in another domain. Moreover, a fusion rule is presented to integrate the results of the identification performed from several sensors in a distributed radar system. Tests performed both on simulated signals and on real signals acquired from a scale model of a helicopter, confirm the validity of the algorithm. Finally, a waveform design framework for joint radar-communication systems is presented. The waveform is composed by quasi-orthogonal chirp sub-carriers generated through 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. Techniques aimed at optimise the design parameters and mitigate the Inter-Carrier Interference (ICI) caused by the quasiorthogonality of the chirp sub-carriers are also described. The FrFT based waveform is extensively tested and compared with Orthogonal Frequency Division Multiplexing (OFDM) and LFM waveforms, in order to assess both its radar and communication performance.This Thesis presents advanced signal processing solutions for Automatic Target Recognition (ATR) operations and for spectrum sharing in distributed radar systems. Two Synthetic Aperture Radar (SAR) ATR algorithms are described for full- and single-polarimetric images, and tested on the GOTCHA and the MSTAR datasets. The first one exploits the Krogager polarimetric decomposition in order to enhance peculiar scattering mechanisms from manmade targets, used in combination with the pseudo-Zernike image moments. The second algorithm employs the Krawtchouk image moments, that, being discrete defined, provide better representations of targets’ details. The proposed image moments based framework can be extended to the availability of several images from multiple sensors through the implementation of a simple fusion rule. A model-based micro-Doppler algorithm is developed for the identification of helicopters. The approach relies on the proposed sparse representation of the signal scattered from the helicopter’s rotor and received by the radar. Such a sparse representation is obtained through the application of a greedy sparse recovery framework, with the goal of estimating the number, the length and the rotation speed of the blades, parameters that are peculiar for each helicopter’s model. The algorithm is extended to deal with the identification of multiple helicopters flying in formation that cannot be resolved in another domain. Moreover, a fusion rule is presented to integrate the results of the identification performed from several sensors in a distributed radar system. Tests performed both on simulated signals and on real signals acquired from a scale model of a helicopter, confirm the validity of the algorithm. Finally, a waveform design framework for joint radar-communication systems is presented. The waveform is composed by quasi-orthogonal chirp sub-carriers generated through 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. Techniques aimed at optimise the design parameters and mitigate the Inter-Carrier Interference (ICI) caused by the quasiorthogonality of the chirp sub-carriers are also described. The FrFT based waveform is extensively tested and compared with Orthogonal Frequency Division Multiplexing (OFDM) and LFM waveforms, in order to assess both its radar and communication performance

Investigation of Non-coherent Discrete Target Range Estimation Techniques for High-precision Location

Ranging is an essential and crucial task for radar systems. How to solve the range-detection problem effectively and precisely is massively important. Meanwhile, unambiguity and high resolution are the points of interest as well. Coherent and non-coherent techniques can be applied to achieve range estimation, and both of them have advantages and disadvantages. Coherent estimates offer higher precision but are more vulnerable to noise and clutter and phase wrap errors, particularly in a complex or harsh environment, while the non-coherent approaches are simpler but provide lower precision. With the purpose of mitigating inaccuracy and perturbation in range estimation, miscellaneous techniques are employed to achieve optimally precise detection. Numerous elegant processing solutions stemming from non-coherent estimate are now introduced into the coherent realm, and vice versa. This thesis describes two non-coherent ranging estimate techniques with novel algorithms to mitigate the instinct deficit of non-coherent ranging approaches. One technique is based on peak detection and realised by Kth-order Polynomial Interpolation, while another is based on Z-transform and realised by Most-likelihood Chirp Z-transform. A two-stage approach for the fine ranging estimate is applied to the Discrete Fourier transform domain of both algorithms. An N-point Discrete Fourier transform is implemented to attain a coarse estimation; an accurate process around the point of interest determined in the first stage is conducted. For KPI technique, it interpolates around the peak of Discrete Fourier transform profiles of the chirp signal to achieve accurate interpolation and optimum precision. For Most-likelihood Chirp Z-transform technique, the Chirp Z-transform accurately implements the periodogram where only a narrow band spectrum is processed. Furthermore, the concept of most-likelihood estimator is introduced to combine with Chirp Z-transform to acquire better ranging performance. Cramer-Rao lower bound is presented to evaluate the performance of these two techniques from the perspective of statistical signal processing. Mathematical derivation, simulation modelling, theoretical analysis and experimental validation are conducted to assess technique performance. Further research will be pushed forward to algorithm optimisation and system development of a location system using non-coherent techniques and make a comparison to a coherent approach

Dual operative radar for vehicle to vehicle and vehicle to infrastructure communication

The research presented in this Thesis deals with the concepts of joint radar and communication system for automotive application. The novel systems developed include a joint radar and communication system based on the fractional Fourier transform (FrFT) and two interference mitigation frameworks. In the joint radar and communication system the FrFT is used to embed the data information into a radar waveform in order to obtain a signal sharing Linear Frequency Modulation (LFM) characteristics while allowing data transmission. Furthermore, in the proposed system multi user operations are allowed by assigning a specific order of the FrFT to each user. In this way, a fractional order division multiplexing can be implemented allowing the allocation of more than one user in the same frequency band with the advantage that the range resolution does not depend on the number of the users that share the same frequency band but only from the assigned of the FrFT. Remarkably, the predicted simulated radar performance of the proposed joint radar and communication system when using Binary Frequency Shift Keying (BFSK) encoding is not significantly affected by the transmitted data. In order to fully describe the proposed waveform design, the signal model when the bits of information are modulated using either BFSK or Binary Phase Shift Keying (BPSK) encoding is derived. This signal model will result also useful in the interference mitigation frameworks. In multi user scenarios to prevent mutual radar interference caused by users that share the same frequency band at the same time, each user has to transmit waveforms that are uncorrelated with those of other users. However, due to spectrum limitations, the uncorrelated property cannot always be satisfied even by using fractional order division multiplexing, thus interference is unavoidable. In order to mitigate the interference, two frameworks are introduced. In a joint radar communication system, the radar also has access to the communication data. With a near-precision reconstruction of the communication signal, this interference can be subtracted. In these two frameworks the interfering signal can be reconstructed using the derived mathematical model of the proposed FrFT waveform. In the first framework the subtraction between the received and reconstructed interference signals is carried out in a coherent manner, where the amplitude and phase of the two signals are taken into account. The performance of this framework is highly depend on the correct estimation of the Doppler frequency of the interfering user. A small error on the Doppler frequency can lead to a lack of synchronization between the received and reconstructed signal. Consequently, the subtraction will not be performed in a correct way and further interference components can be introduced. In order to solve the problem of the lack of the synchronization an alternative framework is developed where the subtraction is carried out in non-coherent manner. In the proposed framework, the subtraction is carried out after that the received radar signal and the reconstructed interference are processed, respectively. The performance is tested on simulated and real signals. The simulated and experimental results show that this framework is capable of mitigating the interference from other users successfully.The research presented in this Thesis deals with the concepts of joint radar and communication system for automotive application. The novel systems developed include a joint radar and communication system based on the fractional Fourier transform (FrFT) and two interference mitigation frameworks. In the joint radar and communication system the FrFT is used to embed the data information into a radar waveform in order to obtain a signal sharing Linear Frequency Modulation (LFM) characteristics while allowing data transmission. Furthermore, in the proposed system multi user operations are allowed by assigning a specific order of the FrFT to each user. In this way, a fractional order division multiplexing can be implemented allowing the allocation of more than one user in the same frequency band with the advantage that the range resolution does not depend on the number of the users that share the same frequency band but only from the assigned of the FrFT. Remarkably, the predicted simulated radar performance of the proposed joint radar and communication system when using Binary Frequency Shift Keying (BFSK) encoding is not significantly affected by the transmitted data. In order to fully describe the proposed waveform design, the signal model when the bits of information are modulated using either BFSK or Binary Phase Shift Keying (BPSK) encoding is derived. This signal model will result also useful in the interference mitigation frameworks. In multi user scenarios to prevent mutual radar interference caused by users that share the same frequency band at the same time, each user has to transmit waveforms that are uncorrelated with those of other users. However, due to spectrum limitations, the uncorrelated property cannot always be satisfied even by using fractional order division multiplexing, thus interference is unavoidable. In order to mitigate the interference, two frameworks are introduced. In a joint radar communication system, the radar also has access to the communication data. With a near-precision reconstruction of the communication signal, this interference can be subtracted. In these two frameworks the interfering signal can be reconstructed using the derived mathematical model of the proposed FrFT waveform. In the first framework the subtraction between the received and reconstructed interference signals is carried out in a coherent manner, where the amplitude and phase of the two signals are taken into account. The performance of this framework is highly depend on the correct estimation of the Doppler frequency of the interfering user. A small error on the Doppler frequency can lead to a lack of synchronization between the received and reconstructed signal. Consequently, the subtraction will not be performed in a correct way and further interference components can be introduced. In order to solve the problem of the lack of the synchronization an alternative framework is developed where the subtraction is carried out in non-coherent manner. In the proposed framework, the subtraction is carried out after that the received radar signal and the reconstructed interference are processed, respectively. The performance is tested on simulated and real signals. The simulated and experimental results show that this framework is capable of mitigating the interference from other users successfully