Comparison of Automotive FMCW and OFDM Radar Under Interference

Automotive radars are subject to interference in spectrally congested environments. To mitigate this interference, various waveforms have been proposed. We compare two waveforms (FMCW and OFDM) in terms of their radar performance and robustness to interference, under similar parameter settings. Our results indicate that under proper windowing both waveforms can achieve similar performance, but OFDM is more sensitive to interference

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

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

Jamming Effects on Hybrid Multistatic Radar Network Range and Velocity Estimation Errors

This research studies the effects of three noise jamming techniques on the performance of a hybrid multistatic radar network in a selection of different electronic warfare (EW) situations. The performance metrics investigated are the range and velocity estimation errors found using the Cramér-Rao lower bounds (CRLBs). The hybrid multistatic network simulated is comprised of a single active radar transmitter, three illuminators of opportunity (IO), a receiver co-located at the active transmitter site, and two separately located silent receivers. Each IO transmits at a unique frequency band commonly used for civilian applications, including Digital Video Broadcasting-Terrestrial (DVB-T), Digital Audio Broadcasting (DAB), and FM radio. Each receiver is capable of receiving signals at all three IO frequency bands as well as the operating frequency band of the active radar transmitter. The investigations included compare the performance of the network at detecting a single flying target under conditions where different combinations of jammer type, operating mode, directivity, and number of jammers operating are used. The performance degradation of the system compared to operation in a non-contested environment is determined and a comparison between the performance of the hybrid multistatic radar with that achievable by a monostatic radar and an active-only multistatic radar network within a selection of contested scenarios is made. Results show that the use of spatially distributed nodes and frequency diversity within the system enable greater theoretical functionality in the presence of jamming over conventional radar systems

Frequency Diverse Array Radar: Signal Characterization and Measurement Accuracy

Radar systems provide an important remote sensing capability, and are crucial to the layered sensing vision; a concept of operation that aims to apply the right number of the right types of sensors, in the right places, at the right times for superior battle space situational awareness. The layered sensing vision poses a range of technical challenges, including radar, that are yet to be addressed. To address the radar-specific design challenges, the research community responded with waveform diversity; a relatively new field of study which aims reduce the cost of remote sensing while improving performance. Early work suggests that the frequency diverse array radar may be able to perform several remote sensing missions simultaneously without sacrificing performance. With few techniques available for modeling and characterizing the frequency diverse array, this research aims to specify, validate and characterize a waveform diverse signal model that can be used to model a variety of traditional and contemporary radar configurations, including frequency diverse array radars. To meet the aim of the research, a generalized radar array signal model is specified. A representative hardware system is built to generate the arbitrary radar signals, then the measured and simulated signals are compared to validate the model. Using the generalized model, expressions for the average transmit signal power, angular resolution, and the ambiguity function are also derived. The range, velocity and direction-of-arrival measurement accuracies for a set of signal configurations are evaluated to determine whether the configuration improves fundamental measurement accuracy

Digital signal processing for fiber-optic communication systems

As the available bandwidth of optical fibers has been almost fully exploited, Digital Signal Processing (DSP) comes to rescue and is a critical technology underpinning the next generation advanced fiber-optic systems. Literally, it contributes two principal enforcements with respect to information communication. One is the implementation of spectrally-efficient modulation schemes, and the other is the guarantee of the recovery of information from the spectrally-efficient optical signals after channel transmission. The dissertation is dedicated to DSP techniques for the advanced fiber-optic systems. It consists of two main research topics. The first topic is about Fast-orthogonal frequency-division multiplexing (OFDM) — a variant OFDM scheme whose subcarrier spacing is half of that of conventional OFDM. The second one is about Fresnel transform with the derivation of an interesting discrete Fresnel transform (DFnT), and the proposal of orthogonal chirp-division multiplexing (OCDM), which is fundamentally underlain by the Fresnel transform. In the first part, equalization and signal recovery problems result from the halved subcarrier spacing in both double-sideband (DSB) and single-sideband (SSB) modulated Fast-OFDM systems are studied, respectively. By exploiting the relation between the multiplexing kernels of Fast-OFDM systems and Fourier transform, equalization algorithms are proposed for respective Fast-OFDM systems for information recovery. Detailed analysis is also provided. With the proposed algorithms, the DSB Fast-OFDM was experimentally implemented by intensity-modulation and direct detection in the conventional 1.55-μm and the emerging 2-μm fiber-optic systems, and the SSB Fast-OFDM was first implemented in coherent fiber-optic system with a spectral efficiency of 6 bit/s/Hz at 36 Gbps, for the first time. In the second part, Fresnel transform from optical Fresnel diffraction is studied. The discrete Fresnel transform (DFnT) is derived, as an interesting transformation that would be potentially useful for DSP. Its properties are proved. One of the attractive properties, the convolution-preservation property states that the DFnT of a circular convolution of two sequences is equal to the DFnT of either one convolving with the other. One application of DFnT is practically utilized in the proposal of OCDM. In the OCDM system, a large number of orthogonal chirped waveforms are multiplexed for high-speed communication, achieving the maximum spectral efficiency of chirp spread spectrum systems, in the same way as OFDM attains the maximum spectral efficiency of frequency-division multiplexing. Owing to the unique time-frequency properties of chirped waveforms, OCDM outperforms OFDM and single-carrier systems, and is more resilient against the noise effect, especially, when time-domain and frequency-domain distortions are severe. Experiments were carried out to validate the feasibility and advantages of the proposed OCDM systems

Modeling and Mitigation of Wireless Communications Interference for Spectrum Sharing with Radar

Due to both economic incentives and policy mandates, researchers increasingly face the challenge of enabling spectrum sharing between radar and wireless communications systems. In the past eight years, researchers have begun to suggest a wide variety of approaches to radar-communications spectrum sharing, ranging from transmitter design to receiver design, from spatial to temporal to other-dimensional multiplexing, and from cooperative to non-cooperative sharing. Within this diverse field of innovation, this dissertation makes two primary contributions. First, a model for wireless communications interference and its effects on adaptive-threshold radar detection is proposed. Based on both theoretical and empirical study, we find evidence for both Gaussian and non-Gaussian communications interference models, depending on the modeling situation. Further, such interference can impact radar receivers via two mechanisms—model mismatch and boost to the underlying noise floor—and both mechanisms deserve attention. Second, an innovative signal processing algorithm is proposed for radar detection in the presence of cyclostationary, linearly-modulated, digital communications (LMDC) interference (such as OFDM or CDMA) and a stationary background component. The proposed detector consists of a novel whitening filter followed by the traditional matched filter. Performance results indicate that the proposed cyclostationary-based detector outperforms a standard equivalent detector based on a stationary interference model, particularly when the number of cyclostationary LMDC transmitters is small and their interference-to-noise ratio (INR) is large relative to the stationary background