Linear Frequency Modulated Continuous Wave Research Articles

Detection of Fast-Moving and Accelerating Target Using Linear Frequency-Modulated Continuous-Wave Radars

Detection of Fast-Moving and Accelerating Target Using Linear Frequency-Modulated Continuous-Wave Radars

Enhancing Sustainable Transportation with Advancements in Photonic Radar Technology with MIMO and IIR Filtering for Adverse Weather Conditions

Sustainable transportation is crucial in addressing global road safety and environmental challenges. This study introduces a novel photonic radar system, leveraging Linear Frequency-Modulated Continuous Wave (LFMCW) technology for high-speed data transmission. Operating in a homodyne configuration, this system uses a single oscillator to generate both signal and reference waveforms. It incorporates mode division multiplexing (MDM) to enable the detection and ranging of multiple targets, even under adverse atmospheric conditions. To counter atmospheric attenuation, the system is equipped with a 2 × 2 MIMO technique and an Infinite Impulse Response (IIR) filter. Numerical simulations demonstrate the system’s superior performance in range resolution and target detection, achieving significant power improvements. The IIR filter further enhances detection, achieving a power improvement of 200% for target 1 and 276% for target 2. With low power requirements and enhancement through IIR filter equalization, this system presents a viable option for battery-operated vehicles. This innovative approach offers a low-power high-efficiency solution suitable for battery-operated vehicles, promoting safer and more reliable sustainable transportation.

Synthetic Aperture Ladar Motion Compensation Method Based on Symmetric Triangle Linear Frequency Modulation Continuous Wave Segmented Interference

Synthetic Aperture Ladar (SAL) is a sensor that combines laser detection technology with synthetic aperture technology to achieve ultra-high-resolution imaging. Due to its extremely short wavelength, SAL is more sensitive to motion errors. The micrometer-level motion will affect the target’s azimuth focus. This article proposes an SAL motion compensation method based on Symmetric Triangular Linear Frequency Modulation Continuous Wave (STLFMCW) segmented interference, utilizing the characteristics of a triangular wave, to solve the problem of target azimuth defocusing. This article first establishes an STLFMCW echo signal model based on the SAL system under the influence of motion errors. Secondly, the radial velocity gradient along the azimuth direction is extracted using the triangular-wave-positive and -negative frequency modulation signals segmented interference method. Then, for the initial phase wrapping problem, the frequency spectral cross-correlation method is used to accurately estimate the initial radial velocity error. The radial velocity gradient is integrated along the azimuth to obtain the platform motion trajectory. Finally, the compensation functions are constructed to complete the echo Range Cell Migration (RCM) correction and residual phase compensation, resulting in a focused SAL image. This article verifies the practical effect of this method in eliminating motion errors using only one-period STLFMCW signal through simulation and real experiments. The quantitative results show that compared with the traditional method, the proposed method reduces the azimuth Peak Sidelobe Ratio (PSLR) by 8dB and the Integrated Sidelobe Ratio (ISLR) by 9 dB. This method has significant improvements and is of great significance for high-resolution FMCW SAL imaging.

Target Detection in Challenging Environments: Photonic Radar with a Hybrid Multiplexing Scheme for 5G Autonomous Vehicles

The rapid deployment of 5G autonomous vehicles has placed a premium on low-latency communication and reliable sensor technologies for the real-time mapping of road conditions, aligning with sustainability objectives in transport. In response to this imperative, photonic-based radar systems have emerged as an increasingly attractive solution, characterized by their low power consumption and cost-effectiveness. This study delves into the application of linear frequency-modulated continuous wave (FMCW) techniques within photonic radar sensors for the precise detection of multiple targets. Our proposed system seamlessly integrates mode-division multiplexing (MDM) and polarization-division multiplexing (PDM) to achieve a robust target detection capability, contributing to sustainable traffic management. To assess its effectiveness, we rigorously evaluated the system’s performance under challenging conditions, marked by a high atmospheric attenuation of 75 dB/km and a low material reflectivity of 20%. Our results unequivocally demonstrate the efficacy of the MDM-PDM photonic radar in successfully detecting all four specified targets, underscoring its potential to enhance road safety in the realm of autonomous vehicles. The adoption of this technology supports sustainable mobility by mitigating human errors and optimizing the real-time mapping of road conditions.

Doppler Factor in the Omega-k Algorithm for Pulsed and Continuous Wave Synthetic Aperture Radar Raw Data Processing

Synthetic aperture radar (SAR) raw data do not have a direct application; therefore, SAR raw signal processing algorithms are used to generate images that are used for various required applications. Currently, there are several algorithms focusing SAR raw data such as the range-Doppler algorithm, Chirp Scaling algorithm, and Omega-k algorithm, with these algorithms being the most used and traditional in SAR raw signal processing. The most prominent algorithm that operates in the frequency domain for focusing SAR raw data obtained by a synthetic aperture radar with large synthetic apertures is the Omega-k algorithm, which operates in the two-dimensional frequency domain; therefore, in this paper, we used the Omega-k algorithm to produce SAR images and modify the Omega-k algorithm by adding the Doppler factor to improve the accuracy of SAR raw data processing obtained by the continuous wave and pulsed frequency modulated linear frequency modulated radar system from the surfaces of interest. On the other hand, for the case of unmanned aerial vehicle-borne linear frequency modulated continuous wave (LFM-CW) SAR systems, we added motion compensation to the modified Omega-k algorithm. Finally, the testing and validation of the developed Omega-k algorithm used simulated and real SAR raw data for both pulsed synthetic aperture and continuous wave radars. The real SAR raw data used for the validation of the modified Omega-k algorithm were the raw data obtained by the micro advanced synthetic aperture radar (MicroASAR) system, which is an LFM-CW synthetic aperture radar installed on board an unmanned aerial system and the raw data obtained by European remote sensing (ERS-2) satellite with a synthetic aperture radar installed.

Micro-Doppler Signature Detection and Recognition of UAVs Based on OMP Algorithm.

With the proliferation of unmanned aerial vehicles (UAVs) in both commercial and military use, the public is paying increasing attention to UAV identification and regulation. The micro-Doppler characteristics of a UAV can reflect its structure and motion information, which provides an important reference for UAV recognition. The low flight altitude and small radar cross-section (RCS) of UAVs make the cancellation of strong ground clutter become a key problem in extracting the weak micro-Doppler signals. In this paper, a clutter suppression method based on an orthogonal matching pursuit (OMP) algorithm is proposed, which is used to process echo signals obtained by a linear frequency modulated continuous wave (LFMCW) radar. The focus of this method is on the idea of sparse representation, which establishes a complete set of environmental clutter dictionaries to effectively suppress clutter in the received echo signals of a hovering UAV. The processed signals are analyzed in the time-frequency domain. According to the flicker phenomenon of UAV rotor blades and related micro-Doppler characteristics, the feature parameters of unknown UAVs can be estimated. Compared with traditional signal processing methods, the method based on OMP algorithm shows advantages in having a low signal-to-noise ratio (-10 dB). Field experiments indicate that this approach can effectively reduce clutter power (-15 dB) and successfully extract micro-Doppler signals for identifying different UAVs.

Efficient binary sequence set designs for MIMO PMCW radar

Multiple-input multiple-output (MIMO) phase-modulated continuous wave (PMCW) radar systems have major advantages for mutual-interference mitigation over their linear frequency-modulated continuous wave (LFMCW) counterparts. To attain a virtual array length of M×M̃ with M transmit and M̃ receive antennas, a probing sequence set with both low auto-correlation sidelobes and low cross-correlations is needed for MIMO PMCW radar. To reduce the hardware cost of sequence generation, binary probing sequence (BPS) sets are desirable. We present herein four efficient computational algorithms to generate BPS sets with desirable properties, and arbitrary sequence lengths and arbitrary number of sequences in the set are allowed. When initialized by random BPS sets, they can be used to obtain many different BPS sets with similar properties, i.e., with large diversity. Moreover, fast Fourier transform (FFT) are exploited, making the algorithms computationally efficient. They can be used to design long BPS sets that are hardly possible using existing methods in the literature. The convergence properties and the relationships among the proposed algorithms are also analyzed under a unified framework. Numerical examples are included to illustrate the effectiveness of our designs.

Radiofrequency Doppler echocardiography

An individual’s respiration and heart rates can be monitored in a contactless manner via Doppler radar. However, previous studies have failed to analyse cardiac activity based on the velocity of myocardial motion. In this study, a linear frequency-modulated continuous wave (FMCW) radar sensor is applied to demonstrate radiofrequency Doppler echocardiograms (RFDEs). An energy-focusing algorithm is proposed to finely select the target range bin. A high signal-to-noise rate signal is achieved and accurate Doppler cardiograms (DCGs) are obtained. The changes in the RFDEs are interpreted and labelled on the corresponding cardiac cycles in the electrocardiogram. In addition, data from different respiratory depths were collected and analysed. Several individuals were monitored over three consecutive days to validate the stability of the RFDE. The results suggest that RFDE can represent the heart cycle and may serve as auxiliary diagnostic tool for identifying cardiac systolic and diastolic defects.

Research on the Safety Alarm Distribution and Control System of Electric Construction Machinery Based on Edge Computing Technology

Aiming at the alarm system of electrical construction machinery, which is mostly developed based on the principle of near electric alarm in the current market, a more excellent safety system is developed: research on the safety alarm distribution and control system of electric construction machinery based on edge computing technology. The X-band-based linear frequency modulation continuous wave (LFMCW) ranging radar is selected as the basic detection method. The system consists of the front-end monitoring device, signal processing and display, and acoustic and optical alarm equipment. To carry more new functions in the future, the front-end monitoring device adopts edge computing technology to overcome the shortcomings of centralized cloud computing. In the application test, the system has high detection accuracy and high practical use value, which can improve the safety of field operations, reduce the burden of safety supervision, and has good promotion value.

Phase-Coded FMCW for Coherent MIMO Radar

The phase-coded linear-frequency-modulated continuous-wave (PC-FMCW) waveform with a low sampling processing strategy is studied for coherent multiple-input multiple-output (MIMO) radar. The PC-FMCW MIMO structure, which jointly uses both fast-time and slow-time coding, is proposed to reduce sidelobe levels while preserving high range resolution, unambiguous velocity, good Doppler tolerance, and low sampling needs. The sensing performance and practical aspects of the introduced PC-FMCW MIMO structure are evaluated theoretically and verified experimentally. The numerical simulations and experiments demonstrate that the proposed MIMO keeps the advantages of the linear-frequency-modulated continuous-wave (LFMCW) waveform, including computational efficiency and low sampling demands, while having the ability to provide low sidelobe levels with simultaneous transmission.

Method of 2-D Range-Doppler Imaging for Plasma Wake Based on Range Walk Correction

When a hypersonic vehicle flies in the atmosphere, plasma sheath and trails are configured around the vehicle due to aerodynamic heating and ablation, which distort the radar echo signal and then influence the target range information and Doppler frequency extracted from the echoes. In order to examine the impact of plasma laminar wake on radar detection, this article is primarily aimed to establish a laminar wake echo model based on a linear frequency-modulated continuous wave (LFMCW) radar, which takes into account the reaction control system of laminar wake by employing the Born approximation solution and the characteristics of the inhomogeneous and nonunique velocity of the wake medium. An echo signal processing method is also developed, in which the stretch processing technique is combined with the keystone transform of the target range walk correction. Such a treatment not only reduces the sampling rate and bandwidth, but also eliminates the cross-range cells phenomenon caused by hypersonic; finally, the range-Doppler (RD) image of the wake is achieved by 2-D fast Fourier transform (2-D FFT) processing, and radar range and velocity measurement results in the presence of plasma are obtained.

Scanning Microwave Vibrometer: Full-Field Vibration Measurement via Microwave Sensing With Phase-Encoded Beam Scanning

Full-field and remote vibration measurement are highly desirable for various fields from the natural world to engineering. However, traditional techniques such as laser and vision-based approaches suffer from fundamental problems especially in large-scale measurement and harsh environment adaptability. In this article, we develop a novel microwave sensing-based vibration measurement approach with fast phase-encoded synthesis beam scanning, creating a unique scanning microwave vibrometer (SMV). In SMV, we measure the vibration displacement under the sensing mechanism with coherently synthesized linear frequency-modulated continuous wave (LFMCW) radio signals. To this end, we establish the theoretical basis and extraction method of full-field vibration measurement with synthesis beam scanning, following with the detailed procedures for performing the SMV method, which possesses an attractive capability of tricky coupling clutter elimination and remote vibration sensing. In addition, the main considerations of real-life measurement are deeply illustrated. Experimental results with various scenarios are provided to demonstrate the performance of the SMV method, offering a promising approach for contactless full-filed and remote vibration measurement.

Multidomain Fusion Method for Human Head Movement Recognition

In this article, we consider the problem of human head movement recognition (HMR) using linear frequency-modulated continuous-wave (LFMCW) radar. The multidomain fusion network is proposed to improve the HMR performance, which extracts and fuses the multidomain features from the range and time–frequency (TF) domain. Specifically, the 2-D convolutional neural network (2D-CNN) structure is applied to extract range domain features, and the 3-D convolutional neural network (3D-CNN) structure is designed to extract multitype TF representation (TFR) plots features cooperatively. After that, the learnable convolution weights are used for the adaptive fusion of multidomain features. In addition, the attention mechanism is employed to remove redundant information in the fused features. Finally, experimental results on real data verify the effectiveness of the proposed method.

Characterization of the Frequency Ramp Nonlinearity Impact on the Range Estimation Accuracy and Resolution in LFMCW Radars

The ranging accuracy and range resolution in linear-frequency-modulated continuous-wave (LFMCW) radars are vulnerable to the nonlinearity of the transmitted frequency ramp. The frequency ramp nonlinearity (FRN) leads to the degradation of accuracy in range estimation and deteriorates the range resolution in LFMCW radars, which becomes even worse as the target range increases. The uncertainty of the type of FRN makes the problem more complicated. This paper proposes a new range-dependent resolution model and a new range-dependent accuracy model based on the theoretical analysis and experimental evaluations, which characterizes the impact of different types of FRN on the range resolution and accuracy in LFMCW radars. The proposed models have established the quantitative relationship between the FRN, the target distance, and the range accuracy and resolution. A nonlinearity index is utilized in the analysis to quantify the extent of FRN. Moreover, a novel design methodology is also proposed which may guide the design of LFMCW radars under the influence of FRN. Four typical types of FRN that are reasonable in practical LFMCW radars are taken into consideration in both simulations and experiments to validate the proposed theory and methodology.

Photonics-aided integrated sensing and communications in mmW bands based on a DC-offset QPSK-encoded LFMCW.

The evolution of mobile communications towards millimeter-wave (mmW) bands provides a strong opportunity for the seamless integration of radar and wireless communications. We present a photonics-aided mmW integrated sensing and communications (ISAC) system constructed by photonic up-conversion using a coherent optical frequency comb, which facilitates zero frequency offset of the resulting mmW signal. The sensing and communications functions are enabled by a joint waveform that encodes a DC-offset QPSK signal on a linear frequency-modulated continuous wave (LFMCW) in baseband. The QPSK encoding ensures the constant envelope of the mmW ISAC signal for long-distance radar detection. The optimized DC offset preserves the distinctive chirp phase and good cross-correlation of the original LFMCW, which can achieve high-resolution sensing by radar de-chirping and assist in communication sequence synchronization by pulse compression, respectively. Experimental results show that the single-user detection with less than 20-mm sensing error and dual-user detection with a 10.4-cm ranging resolution are realized at 28-GHz band, respectively. The wireless communication with a 11.5-Gbit/s transmission rate also at 28-GHz band is successfully tested. Moreover, the proof-of-concept experiments demonstrate the good frequency tunability and wavelength tolerance of the proposed ISAC system.

3D microwave vibrometer: Contactless three-dimensional vibration measurements using microwave radars

The emerging radar-based vibration measurement technology has attracted much interest in a wide spectrum of applications, such as mechanical test, structural health monitoring, machine diagnosis and vital sign detection. Advances in large monitoring range, high accuracy and excellent test efficiency and environmental adaptability have allowed radar-based vibration measurement method to perform enough superiority over traditional contact measurements like accelerometers or optical ways such as laser triangulation sensors or video/image-based measurements. However, the state of the art for radar vibration measurements mostly focuses on the quantification of one-dimensional vibrational measurement. This paper aims to present an accurate three-dimensional (3D) vibration measurement approach using three microwave radars via linear frequency modulated continuous wave (LFMCW) radars. The system overview and fundamental concept are illustrated firstly. To achieve 3D space trajectory and displacement of a vibrating target, we show the detailed procedures about coordinate system establishment and 3D displacement reconstruction process. Moreover, the error factors and analysis involved in our method are also discussed, allowing robust and accurate measurement for practical applications. Simulation and experimental validations are provided for demonstrating the performance of the method, offering a desired approach for contactless 3D vibration and displacement measurement.

Rapid Linear Frequency Swept Frequency-Modulated Continuous Wave Laser Source Using Iterative Pre-Distortion Algorithm

We present a simple iterative pre-distortion algorithm for achieving a rapid linear frequency sweep of semiconductor lasers. The algorithm achieves the desired frequency swept linearity with only four iterations. We derive a general formula for iterative pre-distortion by establishing the relationship between the laser output frequency and the drive current. The linear frequency-swept laser source obtained by this algorithm can be used in FMCW LiDAR systems. Experimentally, we investigated the algorithm using a 1550 nm distributed feedback (DFB) laser, achieving frequency swept excursion of 30.26 GHz, and frequency swept slope of 504 THz/s. We analyzed the linearity of the frequency swept results for the fourth iteration, achieving less than 5 MHz root mean square (RMS) value of frequency swept nonlinearity.

Deep Learning Based Detection for Communications Systems With Radar Interference

Due to the increasing demand for spectrum resources, the co-existence of communications and radar systems has been proposed that allows radar and communications systems to operate in the same frequency band. On the other hand, deep learning has shown great potential in revolutionizing communications systems. In this work, we investigate the use of deep learning in communications systems subject to interference from radar systems. Specifically, we consider a single-carrier communications system. Linear frequency-modulated (LFM) and frequency-modulated continuous-wave (FMCW) are considered for radar. Several important system parameters, including the level of noise and interference, the radar interference coverage, the symbol duration, feature extraction methods and the number of hidden layers are investigated for the performance of the detector. Fully connected deep neural network (FCDNN) and long short-term memory (LSTM) detectors are implemented, where principle component analysis (PCA) is applied to preprocess the observed signals for the FCDNN detector. Numerical results show that the learning-based detector achieves comparable performance in the radar-communication system to the traditional detector but without interference cancellation. Preprocessing the received signals with PCA can improve the performance of FCDNN when interference is strong. Also, LSTM shows more robust performance than FCDNN when the channel has time-related distortion.

Linearization of nonlinear frequency modulated continuous wave generation using model-based reinforcement learning.

The prevalence of machine learning (ML) opens up new directions for plenty of scientific fields. The development of optics technologies also benefits from it. However, due to the complex properties of nonlinear and dynamic optical systems, optical system control with ML is still in its infancy. In this manuscript, to demonstrate the feasibility of optical system control using reinforcement learning (RL), i.e., a branch of ML, we solve the linearization problem in the frequency modulated continuous wave (FMCW) generation with the model-based RL method. The experiment results indicate an excellent improvement in the linearity of the generated FMCW, showing a sharp peak in the frequency spectrum. We confirm that the RL method learns the implicit physical characteristics very well and accomplishes the goal of the linear FMCW generation effectively, indicating that the marriage of ML and optics systems could have the potential to open a new era for the development of optical system control.

An Applied Frequency Scaling Algorithm Based on Local Stretch Factor for Near-Field Miniature Millimeter-Wave Radar Imaging

The frequency scaling algorithm (FSA) is a popular imaging algorithm for dechirped SAR data. To obtain a large azimuth detection area, the miniature millimeter-wave (mmW) linear-frequency-modulated continuous-wave (LFMCW) surveillance radar requires a wider azimuth beamwidth, which leads to additional range frequency aliasing in FSA. Because of the adoption of the dechirp-on-receive technique, the sampling frequency is much smaller than the range bandwidth during near-field imaging, which further aggravates the aliasing effects. The target cannot be well focused, and it makes the weak targets submerged in the background. To acquire high-quality SAR images, an improved FSA using the local stretch operation is proposed. The aliasing bandwidth properties introduced by the FS operation and the desired objective range cell migration (RCM) factor are used in this proposed local-stretch FSA (LSFSA). The initial RCM factor is adjusted by the stretch operation to eliminate the frequency aliasing to a certain level without increasing the computing load. The LSFSA is suitable for solving the problem of range frequency aliasing in near-field side-looking SAR and high squint SAR with wide azimuth beamwidth. The proposed method is validated using reasonable simulations and convincing experiments.