FMCW Radar System Research Articles

Accelerating Deep Learning in Radar Systems: A Simulation Framework for 60 GHz Indoor Radar

FMCW radar systems are increasingly used in diverse applications, and emerging technologies like JCAS offer new opportunities. However, machine learning for radar faces challenges due to limited application-specific datasets, often requiring advanced simulations to supplement real-world data. This paper presents a setup for generating synthetic radar data for indoor environments, evaluated using CNNs. The setup involves comprehensive modeling, including far-field antenna simulations, variations in human radar cross-section, and detailed representations of indoor environments with their corresponding propagation channel properties. These synthetic data are used to train CNNs, and their performance is assessed on real measurement data. The results demonstrate that CNNs trained on synthetic data can perform well when tested on real measurement data. Specifically, the models trained with synthetic data showed performance comparable to models trained with real measurement data, which required a minimum of 300 samples to reach similar levels of accuracy. This result demonstrates that synthetic data can effectively train neural networks, providing an alternative to real measurement data, particularly when collecting sufficient real-world samples is difficult or costly. This approach significantly reduces the time required for generating datasets, and the ability to quickly label data in simulations simplifies and accelerates post-processing. Additionally, the generated datasets can be made more heterogeneous by introducing varying signal conditions, enhancing the diversity and robustness of the training data.

An MTI-Like Approach for Interference Mitigation in FMCW Radar Systems

An MTI-Like Approach for Interference Mitigation in FMCW Radar Systems

Multipath Signal Mitigation for Indoor Localization Based on MIMO FMCW Radar System

Multipath Signal Mitigation for Indoor Localization Based on MIMO FMCW Radar System

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.

Short-Time Remote Heart Rate Measurement Based on mmWave FMCW Radar Frame Structure

This paper presents a novel method to reduce measurement time for remote heart rate measurement using mmWave FMCW radar. The proposed method is based on the sampling theory and the frame structure of recent FMCW radar systems. The range displacement from heartbeat is measured by 60GHz FMCW radar with a fixed frame interval, 50ms. With additional chirp repetition in each frame, the heartbeat signal can be sampled with increased or decreased interval. By adopting three different sampling rates from a single radar measurement, the resolution of heart rate measurement is improved in a short time, 2.5s. The proposed method is evaluated with a commercial off-the-shelf FMCW radar system and three different human subject, for no respiration and natural status. To evaluate the performance of the proposed method, the heart rate result is compared with ECG sensor and conventional signal processing method. The results show that the proposed method estimates the heart rate with lower error and shorter measurement time.

A Phase Noise Optimized FMCW Radar System for Data Transmission

A Phase Noise Optimized FMCW Radar System for Data Transmission

In-Cabin MIMO Radar System for Human Dysfunctional Breathing Detection

The integration of wireless sensors into the automotive industry is making vehicles increasingly safe and autonomous. At present, vehicles are equipped with external sensors that facilitate maneuverability and braking and internal sensors that detect presence, seat belt state, and occupant vital signs. Early detection of dysfunctional breathing patterns can reduce the risk of accidents caused by drowsiness or fatigue. In this regard, this work presents an MIMO FMCW Radar System able to distinguish dysfunctional breathing patterns from human torso motion. The torso has been divided into six regions, and the amplitude of the elongation and the frequency of motion of each region have been measured during breathing. An elongation map is then constructed in order to graphically show the dysfunctional breathing patterns. The signal processing includes a peak search algorithm to detect elongation amplitude and a bandpass frequency filter to minimize dc components, random driver motion, and vehicle vibration. A torso elongation emulator phantom has been assembled with materials of skin-like relative permittivity and dc motors for calibration and validation of basic breathing patterns. Finally, the signal of the system is compared with that of a commercial respiration belt, and then the system is tested by performing measurements on people. The MIMO radar system is able to measure, differentiate, and classify patterns associated with dysfunctional breathing such as hyperventilation syndrome and thoracic dominant breathing.

빔 스위칭 송신기를 사용한 3차원 탐지 FMCW 레이다 구현

This study proposes a 24 GHz FMCW radar system to detect the 3-dimensional location of a target. To determine the azimuth and elevation angles of a target, the proposed radar includes seven transmitters, illuminating seven elevation angles between −17.5° and 17.5° with a 5° resolution, and a receiver with a 2×4 array. Instead of using a conventional switch, beam steering is performed by directly switching the power amplifier of the transmitter. Experimental results show that the proposed radar system detects the location of the target with an RCS of −12.40 dBsm at a distance of 350 m with 20 dB SNR.

94 GHz 수신 4채널, 송신 1채널 FMCW 레이다 시스템

This paper describes a 94 GHz FMCW radar system for unmanned vehicles using 94 GHz 1 Tx and 4 RX chips designed in a 65-nm CMOS process. The measured output power of the transmitter and the conversion gain of the receiver were 9.77 dBm and 26 dB, respectively. The simulated noise figure of the receiver chip was 8 dB. The Tx and Rx antennas were microstrip patch antennas with a gain of 11 dBi on a Duroid substrate. The chirp period of the sawtooth FMCW waveform was 50 μs. The baseband signal was bandpass-filtered with a passband gain of 26 dB and sampled at a rate of 50 MSPS with a 14-bit ADC. The output of the ADC was acquired using an FPGA. The distance and angle information of the target were calculated using the FFT-based algorithm. The processed results closely matched the calculated results based on the specifications of TRx chips and processing gain, which confirmed the validity of the developed radar system.

(Digital Presentation) Sub-THz Front Ends for Future Communication and Sensing Technologies in 130nm Sige Bicmos Technology

Introduction: Beyond the-5G technologies are targeting the available bandwidth (BW) in the D-band and J-band. This promises for very high speed communication and sensing accuracy. Although the advantages of operating beyond 100 GHz from the application point of view, it requires a lot of research and development to design a reliable and power efficient chipsets. In this presentation we will go through the design of wideband 240 GHz transmitter (Tx) and receiver (Rx). Firstly an overview about the link budget analysis will be given, then the design of the local carrier signal generator will be discussed. The wideband Txs and Rxs are to be presented with frequency channelizing concept. At the end the results of the wireless links will be demonstrated. Link Budget Analysis: Operating at sub-THz frequencies approaching the transistor fT put a lot of constraints on the system link budget. The elevated noise figure together with the limited maximum Pout of the transistors lead to solutions which might be limited in BW or power efficiency. Hence the design architecture need to be optimized taking into account the elevated power consumption and heat dissipation. Carrier Generation: Several approaches could be followed to generate the sub-THz carrier frequency. For a power efficient solution the fundamental oscillators promise for a power efficient solution but with limited phase noise performance and tuning range. Such a solution is more common for imaging systems operating at a single frequency. In order to achieve wider tuning ranges for multi-channel scenario or FMCW radar systems, the frequency multiplication chains are common, whereas the multiplication factor depends on the system parameters. Sub-THz Rx: Different approaches were followed to realize a wideband sub-THz Rx. For some technologies the transistors ft does not promise the realization of low noise amplifiers (LNA) with reasonable noise figure, gain and BW. Hence the mixer first approach were followed trying to optimize the noise figure of the down conversion mixer as much as possible. This also enhances the input compression point (IP1dB) of the Rx which is better for monostatic radar applications. On the other hand, if the technology in use allows the development of well performing LNA’s, the LNA first approach was followed to enhance the all over NF of the receiver and ease the implementation of IQ Rxs. In our work an LNA was implemented followed by IQ downconversion mixers and baseband chain as presented in [3]. Sub-THz Tx: The Tx main challenging performance parameter in the sub-THz frequency range is to achieve high output compression point across the required BW with as high efficiency as possible. Increasing the power handling capabilities of the power amplifiers (PA) by increasing the transistors sizes of the output stages, leads to low output impedance and hence higher impedance transformation ratios for the matching structures and eventually narrow band designs. Hence the power combining architectures were proposed as an alternative to increase the output power either by combining on-chip or combining in air. In this work a fully integrated IQ Tx is to be presented with on-chip LO chain and 4-way power combined power amplifier. Baseband Signal Generation and Processing The baseband topology depend on the application. For mobile communication or localization use cases a wideband channels are not available directly from the digital processors, a kind of channel bonding is required either in the digital domain or in the analog domain. As a proof of concept we present here 3-IQ frequency interleaving combiner. Wireless Link Demonstrator Two demonstrators are to be presented. The first demonstrator is transmitting a broadband IQ signal generated from an arbitrary wave generator wirelessly utilizing an IQ 240GHz Tx and Rx. Data rates up to 100 Gbps were demonstrated across a 1m of wireless link. The second demonstrator includes the implementation of 3-channel IQ channelizer to create the complex modulated signal at several intermediate frequencies (IFs) and then upconverted to the 240GHz carrier signal. On the Rx side the de-channelizer convert the down modulated signal to three IQ channels. Data rates up to 8Gbps were demonstrated wirelessly with the channelization with potential of further enhancements for more channels integration. Outlook The future of the sub-THz wireless links for high speed communication and localizations goes towards implementing phased array and MIMO systems. This requires the research community to develop novel architectures to develop large scale arrays with acceptable power consumptions and suitable packaging solution. On the baseband side also the channel bonding solutions are still in an early stage, requiring more work to bond modularly larger number of channels.

Radar System for Detecting Respiration Vital Sign of Live Victim Behind the Wall

The presence of an obstacle in detecting respiration vital signs using a radar system does not only exhibit attenuation and phase shift effects on the radar signal but also causes additional beat frequencies to appear beside those from the target. When a conventional FMCW radar system detects the peak of the received signal spectrum as a beat frequency, this will give an error of detection. The respiratory vital signs will then be undetectable. A method to overcome this obstacle problem is needed. Therefore the implementation of the FMCW radar system in detecting respiratory vital signs behind the wall can be realized. In this paper, a method to deal with the previously mentioned problem is proposed. The proposed method consists of a method for identifying the obstacle response. Then the results are used to eliminate the beat frequency that arises from the obstacle structure, and therefore the signal to clutter ratio (SCR) can be improved. Furthermore, the method is combined with the phase detection method, which is applied to extract the Doppler response related to the target respiratory vital signs. The weighting process by elaborating cross correlation is also employed for minimizing clutter from other objects reflection under debris. A laboratory experiment by developing an FMCW radar system with a 24 GHz frequency operation was performed in this research. The proposed detection method was elaborated in the post-processing of the radar system. The experiment result demonstrates that the proposed method is capable of eliminating the effect of the wall and successfully extracting the respiration vital sign pattern.

Compressive Sensing-Based SAR Image Reconstruction from Sparse Radar Sensor Data Acquisition in Automotive FMCW Radar System.

In this paper, we propose a method for reconstructing synthetic aperture radar (SAR) images by applying a compressive sensing (CS) technique to sparsely acquired radar sensor data. In general, SAR image reconstruction algorithms require radar sensor data acquired at regular spatial intervals. However, when the speed of the radar-equipped platform is not constant, it is difficult to consistently perform regular data acquisitions. Therefore, we used the CS-based signal recovery method to efficiently reconstruct SAR images even when regular data acquisition was not performed. In the proposed method, we used the l1-norm minimization to overcome the non-uniform data acquisition problem, which replaced the Fourier transform and inverse Fourier transform in the conventional SAR image reconstruction method. In addition, to reduce the phase distortion of the recovered signal, the proposed method was applied to each of the in-phase and quadrature components of the acquired radar sensor data. To evaluate the performance of the proposed method, we conducted experiments using an automotive frequency-modulated continuous wave radar sensor. Then, the quality of the SAR image reconstructed with data acquired at regular intervals was compared with the quality of images reconstructed with data acquired at non-uniform intervals. Using the proposed method, even if only 70% of the regularly acquired radar sensor data was used, a SAR image having a correlation of 0.83 could be reconstructed.

Signal Expansion Method in Indoor FMCW Radar Systems for Improving Range Resolution.

As various unmanned autonomous driving technologies such as autonomous vehicles and autonomous driving drones are being developed, research on FMCW radar, a sensor related to these technologies, is actively being conducted. The range resolution, which is a parameter for accurately detecting an object in the FMCW radar system, depends on the modulation bandwidth. Expensive radars have a large modulation bandwidth, use the band above 77 GHz, and are mainly used as in-vehicle radar sensors. However, these high-performance radars have the disadvantage of being expensive and burdensome for use in areas that require precise sensors, such as indoor environment motion detection and autonomous drones. In this paper, the range resolution is improved beyond the limited modulation bandwidth by extending the beat frequency signal in the time domain through the proposed Adaptive Mirror Padding and Phase Correction Padding. The proposed algorithm has similar performance in the existing Zero Padding, Mirror Padding, and Range RMSE, but improved results were confirmed through the indicating the size of the side lobe compared to the main lobe and the accurate detection rate of the OS CFAR. In the case of , it was confirmed that with single targets, Adaptive Mirror Padding was improved by about 3 times and Phase Correct Padding was improved by about 6 times compared to the existing algorithm. The results of the OS CFAR were divided into single targets and multiple targets to confirm the performance. In single targets, Adaptive Mirror Padding improved by about 10% and Phase Correct Padding by about 20% compared to the existing algorithm. In multiple targets, Phase Correct Padding improved by about 20% compared to the existing algorithm. The proposed algorithm was verified through the MATLAB Tool and the actual FMCW radar. As the results were similar in the two experimental environments, it was verified that the algorithm works in real radar as well.

A Cooperative Radar System With Active Reference Target Synchronization for Kinematic Target Analysis

This article presents a short-range cooperative radar system in the 77-GHz band for the estimation of kinematic parameters, such as position, velocity, and acceleration of a target. The proposed system uses two FMCW radar sensors that are operated incoherently and only depend on a common trigger for coarse synchronization. The resulting frequency offset and phase offset in the beat spectrum of the radar sensors are eliminated through calibration with a known active reference target. For easy detection of the reference target in the beat spectrum, a novel interchirp modulation method is proposed. The sampled data of a single receive channel of only one of the sensors of the system allow for a complete estimation of the kinematic target parameters. The theoretical analysis of incoherent FMCW radar systems is carried out, and the constraints and signal processing algorithms are derived from the results. The theory and operating principle of the proposed system are verified through measurements in an anechoic chamber. The accuracies for the position, velocity, and direction of movement (DoM) estimation are better than 10 mm, 0.03 m/s, and 1.4°, respectively.

Automatic Recognition of Basic Strokes Based on FMCW Radar System

It has been demonstrated the advantage of basic stroke recognition algorithm in the field of human-computer interaction (HCI). However, most traditional techniques heavily rely on the touch-contact operations to obtain character information, which limits the further application in non-contact scenario such as germ infection environment, high/low temperature environment or scene for blind human. This paper proposes a non-contact and automatic basic stroke recognition algorithm for handwritten Chinese characters based on frequency modulated continuous wave (FMCW) radar system. First, the radar system collects intermediate frequency (IF) signal of the eight basic strokes given as follows: <fig orientation="portrait" position="float" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <graphic orientation="portrait" position="float" xlink:href="hou17-3071884.eps"/> </fig> (horizontal stroke), <fig orientation="portrait" position="float" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <graphic orientation="portrait" position="float" xlink:href="hou18-3071884.eps"/> </fig> (dot stroke), <fig orientation="portrait" position="float" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <graphic orientation="portrait" position="float" xlink:href="hou19-3071884.eps"/> </fig> (lift stroke), <fig orientation="portrait" position="float" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <graphic orientation="portrait" position="float" xlink:href="hou20-3071884.eps"/> </fig> (left falling stroke), <fig orientation="portrait" position="float" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <graphic orientation="portrait" position="float" xlink:href="hou21-3071884.eps"/> </fig> (bend stroke), <fig orientation="portrait" position="float" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <graphic orientation="portrait" position="float" xlink:href="hou22-3071884.eps"/> </fig> (right falling stroke), <fig orientation="portrait" position="float" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <graphic orientation="portrait" position="float" xlink:href="hou23-3071884.eps"/> </fig> (vertical stroke) and <fig orientation="portrait" position="float" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <graphic orientation="portrait" position="float" xlink:href="hou24-3071884.eps"/> </fig> (hook stroke). Second, a range-time sequence (RTS) is obtained from IF signal by the window fast Fourier transform (window-FFT) algorithm, and an azimuth-time sequence (ATS) is obtained from IF signal by the frequency domain Capon (FD-Capon) algorithm. Then, the feature area-framing, binarization and open operation (FA-FBO) algorithm is proposed to enhance the features of the above two sequences. After that, a feature map set containing RTS feature map (RTSFM) and ATS feature map (ATSFM) is obtained. Finally, a novel convolutional neural network (CNN) model is customized to perform the strokes classification task with these feature maps as input. Experimental results demonstrate that the proposed scheme is able to effectively recognize the eight basic strokes and achieve an average classification accuracy of 99.25%.

고해상도 ISAR 영상을 위한 광자 기반 FMCW 송수신 시스템 설계

This paper proposes a design for a photonics-based radar system for high-resolution inverse synthetic-aperture radar (ISAR) images. The proposed radar system can derive broadband characteristics using optical elements, such as phase modulator, laser source, and dual parallel Mach-Zehnder modulator (DPMZM). The detection performance and ISAR images for the target are observed according to the bandwidth of the radar system using modeling and simulation (M&amp;S) for the proposed radar system. To verify the effectiveness of the bandwidth of the radar system, the proposed radar system are fabricated, and its performances are measured using a small drone in a practical environment. The results prove that the proposed FMCW radar system is a suitable candidate to overcome the limitations of bandwidth and high resolution.

Towards radar barriers for animal fatality detection at wind turbines: numerical and preliminary experimental results

Bats and birds are endangered by wind turbines, leading to a significant amount of fatalities in recent years, mainly due to a direct collision of the animals with the rotor blades or through barotrauma effects. The search for fatalities and the quantification of their number is an important tool to understand the adverse effects of wind turbines on bats and birds. This method has several problems: Cadavers do not always remain on site due to predators, only a part of the relevant area on the ground can be searched manually and not all fatalities can be found. This leads to the fact that searches, although extremely valuable in the analysis of animal mortality, are hardly used in practice due to the high effort and enormous costs. The present work closes this research gap by proposing a radar barrier approach that automatically detects animal fatality in real-time. Therefore, three FMCW radar systems are attached to the tower of a wind turbine at different heights. Subsequent processing of time-of-flight information enables a binary classification of whether a fatality was observed or not. This study presents the results from numerical simulations as well as preliminary experimental results for a proof of concept.

Millimeter wave radar data of people walking.

This dataset contains complex signals coming from a mmWave FMCW radar system. Signals were acquired during a measurement campaign taken indoor and aimed to assess people's different ways of walking. Measurement setup and devices are described.The dataset consists of the acquisitions of six different types of activities, performed by 29 subjects who repeat each activity several times. Therefore, the dataset contains multiple different experiments for each activity, for a total of 231 acquisitions. The subjects walk without any constraint or do not follow any pattern, thus making this dataset useful not only for human gait recognition but also to evaluate the performance of different radar data processing algorithms.

YOLO-Based Simultaneous Target Detection and Classification in Automotive FMCW Radar Systems.

This paper proposes a method to simultaneously detect and classify objects by using a deep learning model, specifically you only look once (YOLO), with pre-processed automotive radar signals. In conventional methods, the detection and classification in automotive radar systems are conducted in two successive stages; however, in the proposed method, the two stages are combined into one. To verify the effectiveness of the proposed method, we applied it to the actual radar data measured using our automotive radar sensor. According to the results, our proposed method can simultaneously detect targets and classify them with over 90% accuracy. In addition, it shows better performance in terms of detection and classification, compared with conventional methods such as density-based spatial clustering of applications with noise or the support vector machine. Moreover, the proposed method especially exhibits better performance when detecting and classifying a vehicle with a long body.

Analysis of Components and Circuit for FMCW Radar System

Analysis of Components and Circuit for FMCW Radar System