Frequency-modulated Continuous-wave Radar System Research Articles

Time-variant parity-time symmetry in frequency-scanning systems.

Parity-time (PT) symmetry is an active research area that provides a variety of new opportunities for different systems with novel functionalities. For instance, PT symmetry has been used in lasers and optoelectronic oscillators to achieve single-frequency lasing or oscillation. A single-frequency system is essentially a static PT-symmetric system, whose frequency is time-invariant. Here we investigate time-variant PT symmetry in frequency-scanning systems. Time-variant PT symmetry equations and eigenfrequencies for frequency-scanning systems are developed. We show that time-variant PT symmetry can dynamically narrow the instantaneous linewidth of frequency-scanning systems. The instantaneous linewidth of a produced frequency-modulated continuous-wave (FMCW) waveform is narrowed by a factor of 14 in the experiment. De-chirping and radar imaging results also show that the time-variant PT-symmetric system outperforms a conventional frequency-scanning one. Our study paves the way for a new class of time-variant PT-symmetric systems and shows great promise for applications including FMCW radar and lidar systems.

Combining 77–81 GHz MIMO FMCW radar with frequency-steered antennas: a case study for 3D target localization

Abstract In this paper, we introduce a compact 6 × 8 channel multiple-input multiple-output frequency-modulated continuous-wave radar system capable of determining the three-dimensional positions of targets despite utilizing a linear virtual array. The compact system, containing two cascaded radar transceiver ICs, has 48 virtual channels. We conduct a direction of arrival estimation with these virtual channels to determine the azimuth angle. To overcome the spatial limitation of the linear array, we use frequency-steered transmit antennas, which vary their main lobe direction during the frequency chirp, allowing the elevation angle to be determined by using a sliding window fast Fourier transform algorithm. In this study, we present the system’s concept along with the associated signal processing. By taking measurements in different scenarios, each with differently placed corner reflectors, we investigate the capability of the system to separate adjacent targets concerning range, azimuth, and elevation. These measurements are additionally employed to point out the design trade-offs inherent to the system.

FMCW Radar System Interference Mitigation Based on Time-Domain Signal Reconstruction.

In this study, an interference detection and mitigation method is proposed for frequency-modulated continuous-wave radar systems based on time-domain signal reconstruction. The interference detection method uses the difference in one-dimensional fast Fourier transform (1D-FFT) results between targets and interferences. In the 1D-FFT results, the target appears as a peak at the same frequency point for all chirps within one frame, whereas the interference appears as the absence of target peaks within the first or last few chirps within one frame or as a shift in the target peak position in different chirps. Then, the interference mitigation method reconstructs the interference signal in the time domain by the estimated parameter from the 1D-FFT results, so the interference signal can be removed from the time domain without affecting the target signal. The simulation results show that the proposed interference mitigation algorithm can reduce the amplitude of interference by about 25 dB. The experimental results show that the amplitude of interference is reduced by 20-25 dB, proving the effectiveness of the simulation results.

Efficient Clutter Cancellation Algorithm Based on a Suppressed Clutter Map for FMCW Radar Systems

This paper proposes an efficient clutter cancellation algorithm based on suppressed clutter map for frequency-modulated continuous wave radar systems. In conventional clutter cancellation algorithms based on clutter maps, range-Doppler maps are employed. However, if the radar cross section (RCS) of the targets is significantly lower than the RCS of the clutter, a problem may occur in that the targets may also be removed in the clutter-removal process. To solve this problem, the proposed algorithm creates a range-Doppler map to which the moving target indicator (MTI) algorithm is applied instead of the general range-Doppler map that does not include the MTI algorithm. The range-Doppler map, used after applying the clutter suppression filter, significantly reduces the clutter removal effect on targets in which RCS is relatively weak by suppressing the effect of relatively dominant clutter signals. The experimental results showed that the proposed algorithm detects weak targets that remain undetected by the existing map-based clutter-removal algorithm.

Adaptive Nonlinear Least Squares Framework for Contactless Vital Sign Monitoring

The respiratory and heart rates are critical physiological parameters, and conventional contact-based monitoring techniques may cause discomfort and epidermal damage, being therefore inadequate for long-term monitoring. Despite recent advances, accurate contactless vital sign monitoring is still challenging in practical scenarios, especially in relation to heart rate estimation. In this work, we propose a comprehensive framework for vital sign processing in frequency-modulated continuous-wave radar systems and evaluate its performance with real data imitating common working conditions in an office environment. First, to improve the signal-to-noise ratio before estimation, we propose a novel slow-time phase correlation processing, which allows early integration of the vital sign energy at nearby range bins. Subsequently, we present an adaptive nonlinear least squares framework that explores the harmonic structure existing in the recovered displacement signal. An additional Kalman filter stage is designed to select among multiple estimates from different search regions, thus conferring adaptivity and robustness against harmonic interference and noise. This approach largely provides estimates within the predefined error intervals, being capable of tracking the true breathing and heart rate values even during continuous small body movements. The final accuracy and root mean square error values have shown enhanced estimation, outperforming conventional spectral estimation and other recently proposed methods in almost all scenarios.

Multitarget Angle of Arrival Estimation Using Rotating mmWave FMCW Radar and Yolov3

It is still challenging to accurately localize unmanned aerial vehicles (UAVs) from a ground control station (GCS) using various sensors. The mmWave frequency-modulated continuous wave (FMCW) radars offer excellent performance for target detection and localization in harsh environments and low lighting conditions. However, the estimated angle of arrival (AoA) of targets in the captured scene is quite poor. This article focuses on improving AoA estimation by combining the cutting-edge machine learning (ML) algorithms with a mechanical radar rotor setup. An mmWave FMCW radar system is mounted on a programmable rotor to capture range–angle maps of targets at various locations. The range–angle images are then labeled and trained further with the Yolov3 algorithm. Subsequent testing reveals that for detected target objects, the centroid of the bounding boxes from the detected objects provides accurate AoA estimation with very low root mean square error (RMSE). The results show that the proposed approach outperforms traditional methods in terms of performance and estimation accuracy.

Solving Ambiguity in Target Detection for BPSK-Based MIMO FMCW Radar System

In a binary phase shift keying (BPSK)-based multiple-input and multiple-output (MIMO) frequency-modulated continuous wave (FMCW) radar system, real and ghost targets are detected simultaneously, causing ambiguity in target detection. In this paper, we define the targets that are inevitably generated by the BPSK modulation as ghost targets and propose a method for suppressing them. The proposed ghost target suppression method consists of two main steps. First, at the receiving end, a received signal is demodulated using a specific code orthogonal to binary codes used to modulate transmitted signals. With the orthogonality between the codes, only ghost targets remain in the demodulated received signal. Then, by subtracting the demodulated signal including the ghost targets from the initially received signal, only the information of the actual targets can be restored. We verify the performance of the proposed method through simulations and actual signal measurements. In addition, the target estimation performance of the proposed method is compared with that of the time-division multiplexing MIMO FMCW radar system.

Method for Improving Range Resolution of Indoor FMCW Radar Systems Using DNN.

Various studies on object detection are being conducted, and in this regard, research on frequency-modulated continuous wave (FMCW) RADAR is being actively conducted. FMCW RADAR requires high-distance resolution to accurately detect objects. However, if the distance resolution is high, a high-modulation bandwidth is required, which has a prohibitively high cost. To address this issue, we propose a two-step algorithm to detect the location of an object through DNN using many low-cost FMCW RADARs. The algorithm first infers the sector by measuring the distance to the object for each FMCW RADAR and then measures the position through the grid according to the inferred sector. This improves the distance resolution beyond the modulation bandwidth. Additionally, to detect multiple targets, we propose a Gaussian filter. Multiple targets are detected through an ordered-statistic constant false-alarm rate (OS-CFAR), and there is an 11% probability that multiple targets cannot be detected. In the lattice structure proposed in this paper, the performance of the proposed algorithm compared to those in existing works was confirmed with respect to the cost function. The difference in performance versus complexity was also confirmed when the proposed algorithm had the same complexity and the same performance, and it was confirmed that there was a performance improvement of up to five-fold compared to those in previous papers. In addition, multi-target detection was shown in this paper. Through MATLAB simulation and actual measurement on a single target, RMSEs were 0.3542 and 0.41002 m, respectively, and through MATLAB simulation and actual measurement on multiple targets, RMSEs were confirmed to be 0.548265 and 0.762542 m, respectively. Through this, it was confirmed that this algorithm works in real RADAR.

Interference Compression and Mitigation for Automotive FMCW Radar Systems

Millimeter-wave (mm-wave) frequency-modu- lated continuous wave (FMCW) radars are increasingly being deployed for scenario perception in various applications. It is expected that the mutual interference between such radars will soon become a significant problem. Therefore, to maintain the reliability of the radar measurements, there must be procedures in place to mitigate this interference. This article proposes a novel interference mitigation technique that utilizes the pulse compression principle for interference compression and mitigation. The interference in the received time-domain signal is compressed using an estimated matched filter. Afterward, the compressed interference is discarded, and the signal is repaired in the pulse-compressed domain using an autoregressive (AR) model. Since the interference spans fewer samples after compression, the signal can be restored more accurately in the compressed domain. Real outdoor measurements show that the interference is effectively suppressed down to the noise floor using the proposed scheme. A signal to interference and noise ratio (SINR) gain of approximately 14 dB was achieved in the experimental data, supporting this study. Moreover, the results indicate that this method is also applicable to situations where multiple interference sources are present.

An Ultra-Low-Power C-Band FMCW Transmitter Using a Fast Settling Fractional-N DPLL and Ring-Based Pulse Injection Locking Oscillator

Frequency-modulated continuous-wave (FMCW) signals-based radar systems can outrun the optical and ultrasound sensors in dark and severe weather conditions. FMCW radar systems require a fast settling frequency synthesizer to reduce the chirp signal’s inactive and modulation times. This work proposes a new C-B and FMCW Transmitter based on Fast Settling Fractional-N DPLL (FS-FNDPLL) and ring-based pulse injection locking oscillator (R-PILO). The proposed FS-FNDPLL generates an ultra-fast low-noise smooth narrowband chirp by introducing an automatic controller-based TDC switching (AC-TDCSw) scheme in the forward loop of FNDPLL. Also, the proposed FS-FNDPLL employs a new background gain calibrated digital-to-time converter (BGC-DTC) as a fractional divider in the feedback path for the quantization noise cancellation (QNC). The proposed FMCW transmitter uses an R-PILO to produce fast switching adjacent carriers after generating a narrowband chirp using FS-FNDPLL. The main features of the proposed FMCW to accelerate settling time with AC-TDCSw, BGC-DTC and the integration of spur suppressing pulse generator (SSPG) in R-PILO enable ultra-fast chirps with less phase noise and spur levels. The proposed transmitter up-converts the 500[Formula: see text]MHz narrowband chirp signal onto four adjacent carriers for obtaining a 2[Formula: see text]GHz chirp at the C-band. The simulation results prove that the proposed FMCW Transmitter consumes 79[Formula: see text]mW power. Furthermore, the phase noise of the proposed FS-FNDPLL is reduced to [Formula: see text][Formula: see text]dBc/Hz at 1[Formula: see text]MHz. The proposed FS-FNDPLL reduces the settling time to 1[Formula: see text][Formula: see text]s with the introduced AC-TDCSw scheme.

Photonics-Based De-Chirping and Leakage Cancellation for Frequency-Modulated Continuous-Wave Radar System

A photonics-based leakage cancellation and echo signal de-chirping approach for frequency-modulated continuous-wave radar systems is proposed based on a dual-drive Mach-Zehnder modulator (DD-MZM), with its performance evaluated by the radar measurement and imaging. The de-chirp reference signal and the leakage cancellation reference signal are combined and applied to the upper arm of the DD-MZM, while the received signal including the leakage signal and echo signals is applied to the lower arm of the DD-MZM. When the amplitudes and delays of the leakage cancellation reference signal and the leakage signal are precisely matched and the DD-MZM is biased at the minimum transmission point, the leakage signal is canceled in the optical domain. The de-chirped signals are obtained after the leakage-free optical signal is detected in a photodetector. An experiment is performed. The cancellation depth of the de-chirped leakage signal is around 23 dB when the center frequency and bandwidth of the linearly frequency-modulated signal are 11.5 and 2 GHz. The leakage cancellation scheme is used in a radar system. When the leakage cancellation is not employed, the leakage signal will seriously affect the imaging results and distance measurement accuracy of the radar system. When the leakage cancellation is applied, the imaging results of multiple targets can be clearly distinguished, and the error of the distance measurement results is significantly reduced to 10 cm.

Autoencoder-Based Target Detection in Automotive MIMO FMCW Radar System.

In general, a constant false alarm rate algorithm (CFAR) is widely used to automatically detect targets in an automotive frequency-modulated continuous wave (FMCW) radar system. However, if the number of guard cells, the number of training cells, and the probability of false alarm are set improperly in the conventional CFAR algorithm, the target detection performance is severely degraded. Therefore, we propose a method using a convolutional neural network-based autoencoder (AE) to replace the CFAR algorithm in the multiple-input and multiple-output FMCW radar system. In the AE, the entire detection result is compressed at the encoder side, and only significant signal components are recovered on the decoder side. In this work, by changing the number of hidden layers and the number of filters in each layer, the structure of the AE showing a high signal-to-noise ratio in the target detection result is determined. To evaluate the performance of the proposed method, the AE-based target detection result is compared with the target detection results of conventional CFAR algorithms. As a result of calculating the correlation coefficient with the data marked with the actual target position, the proposed AE-based target detection shows the highest similarity with a correlation of 0.73 or higher.

A Novel Methodology for Spectrally Efficient FMCW Radar Systems

In this letter, we present a novel scheme that compresses the transmit bandwidth of frequency modulated continuous wave (FMCW) radar signal by making use of Barker codes and frequency shifts. The proposed system achieves bandwidth compression where the frequency of the signal is modulated over time using one of the Barker code sequences. Therefore, the changes in the slope of the signal are controlled by Barker codes. To avoid ghost targets, small frequency steps are added at the point of discontinuities. The proposed scheme achieves proportionally superior bandwidth compression at a cost of slightly degraded range resolution. The results are validated by implementation of the scheme on hardware and measuring the bandwidth on a spectrum analyzer. Finally, we jointly optimize spectral efficiency and range resolution to determine the optimal length of the Barker sequence. The resulting flexible design is a huge boost to the applicability of existing FMCW radar systems.

Requirement Analysis and Teardrop-Based Design of High Antenna Isolation for FMCW Radar

Frequency-modulated continuous wave (FMCW) radar is widely used in automotive and consumer electronics because of its range, velocity, and angle measurement functionality. In an FMCW radar system, the isolation between transmitting (Tx) and receiving (Rx) subsystems affects the sensitivity of the FMCW system, which directly impacts the system’s overall performance in target detection. The factors that affect system performance include transmitter-to-receiver on-chip coupling and Tx-to-Rx antenna coupling. The on-chip isolation performance is basically fixed once a radar chip is given, but the antenna isolation performance depends on a designed antenna array. Usually, a targeted antenna requirement is first specified, and then the corresponding Tx and Rx antenna array is designed. However, there is no general principle or criteria for specifying a proper antenna isolation requirement in the existing research. In this paper, first, we reveal that the antenna isolation requirement should be set to be almost the same as the given on-chip isolation value, which is very significant as a general guideline in setting a targeted antenna isolation requirement. All current antenna isolation methods cannot reach the level of on-chip isolation in a compactly designed radar system. We further propose a teardrop-based method to provide high antenna isolation. The principle of an antenna isolation requirement and a novel antenna design using teardrops are both analyzed and demonstrated based on a representative 24 GHz FMCW radar. Our teardrop-shaped structure in the mouth of the conventional Vivaldi antenna achieved greater than 50 dB isolation, while the distance between the Tx and Rx antennas could be reduced to 2.1 mm.

Research on a Simulation Model of a Skywave Over-the-Horizon Radar Sea Echo Spectrum

The capability of a skywave over-the-horizon radar (SWR) to achieve the continuous observation of a wide range of ocean dynamics parameters via a single ionospheric reflection has been demonstrated by many scholars. In order to expand the method of SWR detection of ocean dynamics parameters, a simulation model of an SWR sea echo spectrum based on the Barrick sea surface scattering cross-section model (Barrick model) and 3D ray-tracing method, suitable for a narrow-beam, frequency-modulated continuous-wave radar system (FMCW), was established. Based on this model, we simulated ideal and contaminated SWR sea echo spectra, respectively with the 3D electron density data output by the International Reference Ionosphere (IRI) model. Then, we further analyzed the effects of the grazing incidence angle, scattering angle, scattering azimuth angle and fetch length on the sea surface scattering cross-sections, the retrieval precision of the sea surface wind direction, and the root-mean-square (RMS) wave height, using the simulation data calculated by the Barrick model. The results show that these angles and fetch length cause a small expansion and contraction of the scattering cross-section, and have no influence on the retrieval precision of the sea surface wind direction, but will affect the retrieval precision of the RMS wave height; the influence of the grazing incidence angle and scattering angle is ~2.5 times that of the scattering azimuth angle. The ideal SWR sea echo spectrum has small broadening, but the ionosphere phase contamination will cause serious broadening and shifting of the SWR sea echo spectrum, and the higher order nonlinear term has greater contamination.

FMCW Radar Estimation Algorithm with High Resolution and Low Complexity Based on Reduced Search Area.

We propose a frequency-modulated continuous wave (FMCW) radar estimation algorithm with high resolution and low complexity. The fast Fourier transform (FFT)-based algorithms and multiple signal classification (MUSIC) algorithms are used as algorithms for estimating target parameters in the FMCW radar systems. FFT-based and MUSIC algorithms have tradeoff characteristics between resolution performance and complexity. While FFT-based algorithms have the advantage of very low complexity, they have the disadvantage of a low-resolution performance; that is, estimating multiple targets with similar parameters as a single target. On the other hand, subspace-based algorithms have the advantage of a high-resolution performance, but have a problem of very high complexity. In this paper, we propose an algorithm with reduced complexity, while achieving the high-resolution performance of the subspace-based algorithm by utilizing the advantages of the two algorithms; namely, the low-complexity advantage of FFT-based algorithms and the high-resolution performance of the MUSIC algorithms. The proposed algorithm first reduces the amount of data used as input to the subspace-based algorithm by using the estimation results obtained by FFT. Secondly, it significantly reduces the range of search regions considered for pseudo-spectrum calculations in the subspace-based algorithm. The simulation and experiment results show that the proposed algorithm achieves a similar performance compared with the conventional and low complexity MUSIC algorithms, despite its considerably lower complexity.

A Convolutional Neural Network-Based Method for Discriminating Shadowed Targets in Frequency-Modulated Continuous-Wave Radar Systems.

The radar shadow effect prevents reliable target discrimination when a target lies in the shadow region of another target. In this paper, we address this issue in the case of Frequency-Modulated Continuous-Wave (FMCW) radars, which are low-cost and small-sized devices with an increasing number of applications. We propose a novel method based on Convolutional Neural Networks that take as input the spectrograms obtained after a Short-Time Fourier Transform (STFT) analysis of the radar-received signal. The method discerns whether a target is or is not in the shadow region of another target. The proposed method achieves test accuracy of 92% with a standard deviation of 2.86%.

Novel Multiplexing Scheme for Resolving the Velocity Ambiguity Problem in MIMO FMCW Radar Using MPSK Code

For the high-resolution DoA (Direction of Arrival) estimation, various multiplexing schemes are considered for the multi-input multi-output (MIMO) fast chirp frequency-modulated continuous-wave (FMCW) radar. However, current schemes such as time-division multiplexing (TDM) and binary-phase modulation (BPM) may reduce the maximum detectable velocity, which causes the velocity ambiguity problem. As an extension of the BPM scheme to mitigate this issue, we propose a novel multiplexing scheme using M phase-shift keying (MPSK) code which duplicates shifted target peaks at unequal intervals over the velocity domain. The proposed scheme finds the true peaks to resolve the velocity ambiguity problem by the inversion of the circulant matrix with low additional computation. In addition, the successful implementation of the proposed scheme is conducted with 4 by 8 MIMO uniform linear array (ULA) antennas through the state-of-the-art FMCW radar. Finally, the proposed scheme is compared to the conventional TDM based MIMO scheme regarding signal to noise ratio (SNR) and phase calibration issues for moving targets. The proposed scheme is to estimate the accurate 4D information of targets while resolving the velocity ambiguity problem in the MIMO FMCW radar systems.

Photonics-assisted wideband RF self-interference cancellation with digital domain amplitude and delay pre-matching

A photonics-based digital and analog self-interference cancellation approach for in-band full-duplex communication systems and frequency-modulated continuous-wave radar systems is reported. One dual-drive Mach-Zehnder modulator is used to implement the analog self-interference cancellation by pre-adjusting the delay and amplitude of the reference signal applied to the dual-drive Mach-Zehnder modulator in the digital domain. The amplitude is determined via the received signal power, while the delay is searched by the cross-correlation and bisection methods. Furthermore, recursive least square or normalized least mean square algorithms are used to suppress the residual self-interference in the digital domain. Quadrature phase-shift keying modulated signals and linearly frequency-modulated signals are used to experimentally verify the proposed method. The analog cancellation depth is around 20 dB, and the total cancellation depth is more than 36 dB for the 2-Gbaud quadrature phase-shift keying modulated signals. For the linearly frequency-modulated signals, the analog and total cancellation depths are around 19 dB and 34 dB, respectively.

Radar Signal Decomposition in Steering Vector Space for Multi-Target Classification

In automotive frequency-modulated continuous wave radar systems, targets with similar ranges and velocities might be detected as a single target because their target information overlaps on the range-velocity (RV) plane. When the information of multiple targets overlaps on the RV plane, target classification cannot be performed accurately. Therefore, we propose a method to decompose the overlapped target information on the RV plane for effective target classification. To separate each target’s radar signal, we use an orthogonal projection, in which the steering vector formed from the angle information of the desired target is projected onto the kernel space composed of other steering vectors. To verify the performance of the proposed method, a convolutional neural network-based target classification is performed on the decomposed radar signals. Compared to the angle-fast Fourier transform (FFT)-based signal decomposition, the orthogonal projection-based signal decomposition shows higher classification accuracy, which implies that the target information overlapped on the RV plane is effectively separated. When information of two targets is overlapped, the classification accuracy of the proposed method is 5.9%p higher than that of the conventional method. Moreover, when the information of three targets is overlapped, the accuracy is improved by 25.5%p.