Orthogonal Frequency Division Multiplexing Radar Research Articles

A Novel Intrapulse Beamsteering SAR Imaging Mode Based on OFDM-Chirp Signals

The multiple-input multiple-output synthetic aperture radar (MIMO SAR) system has developed rapidly since its discovery. At the same time, the low-disturbance and high-gain requirements of the MIMO system are continuing to increase. Through the application of digital beamforming (DBF) techniques, the multidimensional waveform encoding (MWE) technique can play a key role in MIMO systems, which can greatly improve the system’s performance, especially the multi-mission capability of radar. Intrapulse beamsteering in elevation is a typical form of multi-dimensional waveform encoding which can greatly improve the transmitting efficiency and multi-mission performance of radar. However, because of the high sensitivity of the DBF technique to height, there is significant deterioration in performance in the presence of terrain undulations. The OFDM (Orthogonal Frequency Division Multiplexing) technique is widely used in communication. Due to the similarity of radar and communication systems and the great waveform diversity of OFDM signals, the OFDM radar has recently begun to emerge as a new radar system, simultaneously, the orthogonality of OFDM signals is in the time and frequency domains, and is not affected by terrain undulation. So, this paper proposes a novel radar mode combining intrapulse beamsteering in elevation and OFDM-Chirp signals, that is, the combination of “beam orthogonality” and “waveform orthogonality”, which can greatly improve the performance and fault tolerance to interference signals. In this manuscript, the system working mode and signal processing flow are introduced in detail, and simulations for both point targets and distributed targets are carried out to verify the feasibility of the proposed mode. Simultaneously, a comparison experiment is carried out, which shows the high level of fault tolerance to terrain undulation and the high potential of the proposed radar mode in Earth observation.

Robust Multiplexing Waveform Design for Integrated OFDM Radar and Communication via Complex Weight Optimization

Compared to traditional single orthogonal frequency division multiplexing (OFDM) radar and OFDM communication systems, integrated OFDM radar and communication systems have the advantages of improved sharing of scarce spectrum resources, a simple hardware structure and a reduced interference between signals. In this paper, a constraint relaxation-based robust OFDM multiplexing waveform (ROW-CR) design method for integrated radar and communication systems is proposed. Considering the influence of correlated clutter and jamming signals, transmission and reception models of different system platforms are established by allocating subcarrier complex weights of different antenna signals so as to determine radar conditional mutual information and communication channel capacity parameters. Meanwhile, a restricted closed model is introduced through the limit range of the target frequency response. Then, a robust OFDM waveform optimization problem for integrated radar and communication systems is constructed by the minimax criterion, and the closed-form solution is obtained by adopting an improved method based on trace function properties and constraint relaxation, resulting in a better radar and communication performance trade-off. In addition, a parameter hierarchical optimization-based robust OFDM waveform (ROW-PHO) design method is further explored to reduce the computational complexity, and this method can also ensure a low system performance loss. Finally, the numerical simulation results verify the effectiveness of the proposed methods.

Doppler Robustness of Joint Communication and Radar Systems Using the Wiener Filter

The orthogonal frequency-division multiplexing (OFDM) is a promising waveform for joint radar and communication systems. In this article, a unified approach is proposed to analyse both radar and communication robustness with respect to Doppler mismatch. The analytical study leads to an expression that links the radar performance to the communication one. The performance of a delay-Doppler radar is quantified by modelling the delay response of the OFDM radar with an appropriate random variable. Different delay filters are analysed, among which the Wiener filter. The analytical results are validated by simulations, they show that the radar system benefits from the Wiener filter, and the configurations where this filter outperforms the other ones are outlined.

On the Effects of Range-Doppler Processing for Target Detection in OFDM-Based RadCom

In integrated radar sensing and radio communication (or simply termed RadCom) literature, a standard method is to use orthogonal frequency-division multiplexing (OFDM) waveforms as communication signals and to sense the echoes of this OFDM signal for radar purposes. While OFDM radar is shown to be simple and effective in proper circumstances, its detection performance under multi-scatterer target scenarios has not been investigated thoroughly yet. This letter focuses on this issue, indicating that the 2-D periodogram method, which is the most commonly used detection method for OFDM radars in the literature, performs poorly when the targets consist of multiple scattering centers. Then, an interference-aware adaptive detector is proposed and shown to be robust against such realistic target scenarios. Analytical and simulation results are provided to support the idea.

Enhancing the Dynamic Range of OFDM Radars Using Non-Linear Operation and Symbol-Based Equalization

Due to the increased flexibility in terms of waveform generation, digitally-modulated radar systems are gaining increasing popularity among research and academia. The ability to dynamically allocate frequency and time slots, as well as to employ different coding, enables novel multiplexing techniques for multiple-input-multiple-output radars and sensor networks, compared to state-of-the-art chirp-modulated systems. Another significant benefit is the possibility for joint radar and communication with the same hardware. A popular modulation for digital radar is orthogonal frequency-division multiplexing (OFDM), due to its well-known properties from communication applications. It offers all the above-mentioned possibilities, however OFDM radar has two main drawbacks: high peak-to-average power ratio (PAPR) due to the varying signal envelope which significantly increases the linearity requirements on the analog hardware and reduces the power efficiency, as well as a decoupling of target range and frequency-shift, which eliminates the possibility of using a high-pass filter to suppress close targets and thus decreases the sensor's dynamic range in comparison to conventional frequency-modulated continuous-wave (FMCW). The latter weakness is sometimes also viewed as a positive, due to the fact that range-frequency coupling can lead to undesired effects in some cases. This work addresses both of these problems together, which exist in every real-world OFDM radar sensor, and presents detailed analysis, simulation, characterization and measurement validation results that show how these effects negatively influence the signal quality and the obtained range-Doppler map of an automotive radar. Furthermore, a non-linear operation mode with receiver-sided healing that does not require any additional processing steps or computation power during radar operation is proposed. Its high potential is verified by measurements with a 78 GHz prototype setup in an anechoic chamber with static reflectors, as well as an automotive radar echo generator for dynamic targets and extended ranges.

System architecture for a compact high range resolution frequency comb OFDM radar

AbstractWith increasing demands on resolution and flexibility in current and future radar applications, the focus is moving to digital radar systems such as orthogonal frequency-division multiplexing (OFDM) radars. To achieve high bandwidths and consequently a high range resolution, high sampling rates are needed. To overcome this constraint, an approach called frequency comb OFDM radar has been developed. This paper presents a novel, hardware efficient implementation of such a frequency comb OFDM radar including a novel way of comb generation. Special attention is put on the suppression of unwanted frequency components. Measurements which demonstrate the functionality of the hardware efficient radar system in combination with the frequency comb OFDM technique are presented.

Vehicular Communications Over OFDM Radar Sensing in the 77 GHz mmWave Band

Radar detection and vehicle-to-everything (V2X) communication are two advanced driver-assistance system (ADAS) functions used to improve the safety of the road users and their driving experience. However, the proliferation of radars on vehicles and the functionalities expected for V2X cause several issues like interference and insufficient communication flow. To address these challenges and optimize the use of the electromagnetic spectrum, the mutualization of communication and radar detection functions in the same component using millimeter-wave (mmWave) is proposed. As orthogonal frequency-division multiplexing (OFDM) waveform seems to be the most suitable waveform to enable this cooperation, we propose to investigate the performance of OFDM radar compared to that of current frequency-modulated continuous wave (FMCW) radar. We simulate and analyse the signal-to-noise ratio (SNR) and the probability of detection (PD) of OFDM radar based on the parameters of a current mid-range automotive FMCW corner radar. We observe that FMCW radar has better SNR and PD than OFDM radar under these conditions. However, by applying a coherent integration scheme on receive, the results obtained show that good performance of OFDM radar can be achieved. To check the effect of the parameters used on the communication performance, we provide graphs of the Bit Error Rate (BER). These graphs show that the BER do not suffer from these parameters but rather that they can be beneficial to the communication.

SDFnT-Based Parameter Estimation for OFDM Radar Systems with Intercarrier Interference

The orthogonal frequency division multiplexing (OFDM) radar suffers from severe performance degradation in range-velocity estimation in high mobility scenarios. In this paper, a novel intercarrier interference (ICI)-free parameter estimation method for OFDM radar is proposed. By employing a scale discrete Fresnel transform (SDFnT), the OFDM radar signals are converted to the scale Fresnel domain, and the orthogonality of subcarriers can be recovered with the optimal scale factor. Furthermore, due to the compatibility of the SDFnT and the discrete Fourier Transform (DFT), the proposed method has low computational complexity and high feasibility for OFDM radar implementation. Simulation results show that the proposed SDFnT-based scheme effectively eliminates the ICI effect for single and multiple targets and achieves high accuracy delay-Doppler estimation for OFDM radar systems in circumstances of high velocity and low SNR with consistency and robustness.

Stepped-Carrier OFDM With a Nonlinear Hopping Pattern for Joint Radar and Communications

In this article, a stepped-carrier orthogonal frequency-division multiplexing (OFDM) system with a nonlinear hopping pattern is developed for joint radar and communication (RadCom). In the proposed OFDM-based RadCom system, the carrier frequencies of OFDM symbols for multiple RadCom nodes are orthogonally switched to avoid interference while also maximizing the signal-to-radar interference ratio (SRIR). Differently from conventional linear stepped-carrier OFDM radar that does not consider the communication performance, we first develop a subband allocation method that considers both the radar and the communication performance for multiple RadCom nodes. Channel state information (CSI) of multiple nodes is shared with a centralized server, which then computes the subband allocation strategy that gives the maximum SRIR. Furthermore, a distributed subband allocation strategy based on stateless Q-learning is also proposed, which is suitable when the RadCom nodes do not share their CSI. We also develop the radar signal processing algorithm for range and velocity estimation when the stepped-carrier OFDM waveforms are transmitted through multiple subbands with a nonlinear hopping pattern. Through computer simulations, we confirm that the proposed stepped-carrier OFDM with the nonlinear hopping pattern exhibits a higher achievable sum rate than conventional linear stepped OFDM while not sacrificing the radar performance of target parameter estimation.

Super-Resolution TOA and AOA Estimation for OFDM Radar Systems Based on Compressed Sensing

This article presents a compressed sensing-based time of arrival (TOA) and angle-of-arrival (AOA) estimation algorithm for orthogonal frequency division multiplexing (OFDM) radar systems. The algorithm is designed for noncooperative targets based on a uniform linear array using a cyclic prefix (CP) added OFDM signal. The algorithm makes three key technical contributions. First, the algorithm adopts the CP-based OFDM signal for the radar TOA/AOA estimation to suppress the multitarget interference and the impact of time delay on the subcarrier orthogonality. Second, this article exploits the structure of the CP-OFDM radar signal model to construct the optimization problem of the joint TOA/AOA recovery. The super-resolution AOA estimation is obtained by using a redundant dictionary containing much more basis than the number of antennas. Third, the algorithm proposes an efficient way to solve the optimization by utilizing the properties of the circulant matrix, fast Fourier transform, and Hadamard multiplication. The simulation results indicate the effectiveness of the proposed algorithm.

OFDM Radar With Subcarrier Aliasing—Reducing the ADC Sampling Frequency Without Losing Range Resolution

Many radar applications require a high range resolution, entailing the necessity for a large signal bandwidth. When employing an orthogonal frequency-division multiplexing (OFDM) radar system in its standard implementation, the radar system must operate at a high sampling frequency to ensure covering the entire signal bandwidth, thus imposing significant challenges on its implementation. Therefore, methods for reducing the sampling frequency are topic of recent research. In this work, a method for reducing the analog-to-digital converter (ADC) sampling frequency at the receiver without losing range resolution is proposed. This is achieved by activating only a fraction of the subcarriers at the transmitter, while simultaneously allowing for systematic aliasing due to undersampling in the receiver. This aliasing is designed such that the active subcarriers do not interfere with each other, which ensures a simple separation of them in the frequency domain. The proposed concept, denoted as subcarrier aliasing (SA), allows reducing the ADC sampling frequency in the receiver, but lacks in reducing the digital-to-analog converter (DAC) sampling frequency in the transmitter. However, the key asset of SA-OFDM lies in the properties of its waveform, making it especially suitable for joint radar and communication applications over other waveforms, e.g., stepped-carrier OFDM.

OFDM Radar and Communication Joint System Using Opto-Electronic Oscillator With Phase Noise Degradation Analysis and Mitigation

Orthogonal frequency division multiplexing (OFDM) signal is a superior dual-functional waveform for the integration of radar sensing and communication in intelligent transportation. But the sensitivity to phase noise is a serious issue introducing interference and causing performance degradation during demodulation. In this paper, we explore the essential mechanism of the action and generation of phase noise through theoretical analysis, where the OFDM demodulation process and power spectrum density (PSD) of phase noise is discussed in the frequency domain, and draw the conclusion that high-speed phase jitter will cause unrecoverable deterioration of OFDM demodulation. Therefore, a photonics-aided radar and communication integrated system based on Optoelectronic oscillator (OEO) is proposed. The positive feedback oscillation with long energy storage time make the phase noise pattern of OEO just suitable to against the phase noise sensitivity of OFDM. A proof-of-concept experiment is demonstrated at 24 GHz with 2 GHz bandwidth to verify the radar sensing and communication function. A two-dimensional radar imaging with a range resolution of 0.075 m and velocity resolution of 4.4 km/h, a communication capacity of 6.4 Gbps is obtained. A quantitative performance comparison is also carried out. By using an ordinary microwave source and OEO separately, the demodulation constellation and error vector magnitude (EVM) under different subcarrier spacing is measured and compared. The result is corresponding to our analysis with the EVM decreasing from 12.5% to 4.7% under subcarrier spacing of 125 kHz.

A Dual-Function Massive MIMO Uplink OFDM Communication and Radar Architecture

This paper proposes a joint uplink massive multiple-input-multiple-output (MIMO) communication and orthogonal frequency-division multiplexing (OFDM) radar sensing architecture. Specifically, uplink communication and short-range radar sensing are considered, where the user equipments (UEs) transmit data to the base-station (BS), which simultaneously receives radar returns from the targets over the same subcarriers. Hence, the signals received at each BS antenna include radar returns and communication signals to be processed for extracting the sensing and communication data. The separation and detection of such signals are achieved by utilizing the channel diversity between the UEs and the targets. To this end, the UEs’ signals are first detected and demodulated, and then subtracted from the received signal to acquire the radar returns. Symbol-based radar processing is then employed, as it provides substantial processing gains, and its detection performance is independent of the transmitted radar waveform. Furthermore, self-interference—due to the simultaneous operation of transmit and receive antennas—is taken into account. The communication rate and normalized error of the radar-target channel estimation are mathematically analyzed, and the trade-off between the achievable rate and radar detection performance is demonstrated in terms of the output power of the communication and radar sub-systems and the signal-to-noise ratio.

Multi-output Convolutional Neural Network Based Distance and Velocity Estimation Technique for Orthogonal Frequency Division Multiplexing Radar Systems

The objective of this work is to propose a new method of estimating velocity and distance based on multi-output convolutional neural network (CNN) for orthogonal frequency division multiplexing (OFDM) radars. The two-dimensional (2D) periodogram is extracted from the received reflected waveforms through radar signal processing of received OFDM symbols. Conventionally, constant false alarm rate (CFAR) algorithm is used to estimate distance and velocity of targets. In contrast, this paper proposes a novel deep-learning based approach for the estimation of the targets in OFDM radar systems. The proposed multi-output CNN-based target detector estimates the distance and velocity of the target simultaneously. The proposed technique is verified through computer simulation. The results show that the proposed multi-output CNN-based method demonstrates more accurate distance and speed estimates than the conventional CFAR. Specifically, the distance and speed estimates of the proposed method are 9.8 and 12.3 times accurate, respectively, than those of the conventional CFAR.

Mutual Interference of Automotive OFDM Radars—Analysis and Countermeasures

Due to its noise-like signal property, digital orthogonal frequency-division multiplexing (OFDM) radars are often assumed to be robust against interference. While a lot of research has been carried out for interference between different modulation schemes, the mechanisms of interference from OFDM to OFDM radars have been barely addressed. This paper provides a thorough analysis of mutual OFDM to OFDM interference based on radar measurements using a 4x4 77 GHz multiple-input multiple-output (MIMO) OFDM radar prototype. The effects of interference are described both qualitatively and quantitatively for cyclic-prefix and stepped-carrier OFDM. Second, it is shown that conventional mitigation methods in the spectrogram are not suitable due to the random coding of cyclic-prefix OFDM. As an alternative, the application of adaptive beamforming is proposed and two realization possibilities are provided. Finally, new mitigation strategies in the modulation domain are proposed. They allow to shape interference to specific range-Doppler cells, yielding an interference-free range-velocity map for the area of interest. Additionally, the method may be used as the basis to enable simple conventional interference mitigation strategies.

Coded OFDM Waveforms for MIMO Radars

Emerging digital radar concepts such as orthogonal frequency-division multiplexing (OFDM) allow flexible signal generation. This opens up new opportunities in waveform design in a multiple-input multiple-output (MIMO) system such as introducing coding for signal multiplexing. In this article, coded MIMO OFDM waveforms are proposed and investigated that allow continuous and simultaneous wideband transmission for all transmitters of a multiple transmit and receive antenna array for spatial radar environment perception. Challenges for coded MIMO OFDM radar operation are derived, and three coded MIMO strategies are introduced and analyzed. Their potential is validated and compared to the standard subcarrier interleaving OFDM approach using simulations and measurements of an experimental 4 × <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ 4$</tex-math></inline-formula> MIMO OFDM radar at 77GHz.

Multiple Target Detection For OFDM Radar Based On Convolutional Neural Network

The objective of this paper is to propose a multiple target identification technique for orthogonal frequency division multiplexing (OFDM) radars. First, a 2-D (range &amp; Doppler) periodogram is obtained from the reflected signal through 2-D fast Fourier transform (FFT) of the received OFDM symbols. Usually, the peaks of the periodogram indicates the targets. Conventionally, peak search algorithms are used to find the multiple targets. In this paper, however, a convolutional neural network (CNN) classifier is proposed to identify the targets. The proposed technique does not need any additional information but the 2-D periodogram while the conventional method requires the noise variance as well as the periodogram. The performance is examined through computer simulation. According to the results, if the number of maximum identifiable targets are small, the proposed technique performs well. However, as the number increases, the detection accuracy decreases. In the simulation environments, the proposed method outperforms the conventional one. The proposed OFDM radar technique can be applied to 6G mobile communications to identify the moving targets around the transmitter without additional frequency resource for radar systems.

Compressive Sensing-Based Radar Imaging and Subcarrier Allocation for Joint MIMO OFDM Radar and Communication System.

In this paper, a joint multiple-input multiple-output (MIMO OFDM) radar and communication (RadCom) system is proposed, in which orthogonal frequency division multiplexing (OFDM) waveforms carrying data to be transmitted to the information receiver are exploited to get high-resolution radar images at the RadCom platform. Specifically, to get two-dimensional (i.e., range and azimuth angle) radar images with high resolution, a compressive sensing-based imaging algorithm is proposed that is applicable to the signal received through multiple receive antennas. Because both the radar imaging performance (i.e., the mean square error of the radar image) and the communication performance (i.e., the achievable rate) are affected by the subcarrier allocation across multiple transmit antennas, by analyzing both radar imaging and communication performances, we also propose a subcarrier allocation strategy such that a high achievable rate is obtained without sacrificing the radar imaging performance.

Time-and-Frequency Hybrid Multiplexing for Flexible Ambiguity Controls of DFT-coded MIMO OFDM Radar

A time-and-frequency hybrid multiplexing technique for a multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) radar is proposed. Discrete Fourier transform (DFT)-coded OFDM waveforms are introduced, which allow it to be free from range-dependent angle errors. These are readily used to provide both time-domain multiplexing and frequency-domain multiplexing in the MIMO OFDM radar. The DFT- coded frequency-domain multiplexing shortens the maximum unambiguous range, while the DFT- coded time-domain multiplexing lowers the maximum Doppler ambiguity. A hybrid of both domain multiplexing techniques can mitigate the respective limitations by adaptively selecting the proper DFT matrix size in each multiplexing domain. This allows to solve the intrinsic range and Doppler ambiguity problems of MIMO radars by controlling the hybrid ratio of the two kinds of DFT- code based multiplexing methods. Range-Doppler and range-angle maps of four examples with different hybrid multiplexing ratios are simulated with a MIMO OFDM radar numerical platform.

Synthetization of Virtual Transmit Antennas for MIMO OFDM Radar by Space-Time Coding

Recent publications have investigated and demonstrated new digital modulation techniques that allow realization of orthogonal frequency division multiplexing (OFDM) radar with relatively low hardware effort. This is especially interesting as the digitally defined signals offer additional freedom for multiplexing schemes of multiple-input multiple-output (MIMO) radar sensors. MIMO radar sensors rely on strictly orthogonal signals to distinguish between multiple transmitters (TX). To span a virtual array with a maximum number of antenna positions, a novel method that combines orthogonal signals with strongly correlated signals generated by space-time coding (STC) is introduced. This leads to virtual transmit antenna positions that are used to improve the unambiguous angular area of an otherwise ambiguous MIMO antenna array. The proposed method is validated with an integrated OFDM radar at millimeter-wave frequencies.