Frequency Modulated Continuous Waveform Research Articles

Classification of Interference Signal for Automotive Radar Systems With Convolutional Neural Network

When a radar signal generated by another vehicle arrives at an ego-vehicle, mutual interference occurs, which can seriously degrade the detection performance of the radar. To mitigate mutual interference, the type of radar modulation used in the interference vehicle must be identified because the types of radar systems installed in each vehicle are different. Therefore, in this paper, we propose a method for classifying the modulation types of interference signals in automotive fast chirp frequency modulated continuous waveform (FMCW) radar systems. We build a mathematical model of the received signal when the radar signal transmitted by the ego-vehicle interferes with various types of interference signals, such as unmodulated continuous wave (CW), slow chirp FMCW, fast chirp FMCW, pulsed CW, and frequency-shift keying signals. In the fast chirp FMCW radar systems, the received signal is converted into range-Doppler response using two-dimensional Fourier transform. Based on range-Doppler responses of the interference signals, we design a classifier to identify the modulation type of interference signals using a convolutional neural network (CNN). Through our proposed CNN, we can classify five different types of interference signals with an accuracy of over 96%. In addition, compared to conventional feature-based machine learning techniques such as support vector machines, the proposed method can effectively identify the interference signal with fewer input signals in shorter time.

High Fidelity Physics Simulation of 128 Channel MIMO Sensor for 77GHz Automotive Radar

Automotive radar is one of the enabling technologies for advanced driver assistance systems (ADAS) and subsequently fully autonomous vehicles. Along with determining the range and velocity of targets with fairly high resolution, autonomous vehicles navigating complex urban environments need radar sensors with high azimuth and elevation resolution. Size and cost constraints limit the physical number of antennas that can be used to achieve high resolution direction-of-arrival (DoA) estimation. Multiple-input/multiple-output (MIMO) schemes achieve larger virtual arrays using fewer physical antennas than would be needed for a single-input/multiple-output (SIMO) system. This paper presents a high-fidelity physics simulation of a 77GHz, frequency-modulated continuous-waveform (FMCW)-based 128 channel (8 transmitters (T x ), 16 receivers (R x )) MIMO radar sensor. The 77GHz synthetic radar returns from full scale traffic scenes are obtained using a high-fidelity physics, shooting and bouncing ray electromagnetics solver. A fast Fourier transform (FFT) based signal processing scheme is used across slow-time (chirp) and space (channel) to obtain range-Doppler and DoA maps, respectively. Detection and angular separation performance comparisons of 16, 64 and 128 channel MIMO radar sensors are made for two complex driving scenarios.

A Self-Calibrated 16-GHz Subsampling-PLL-Based Fast-Chirp FMCW Modulator With 1.5-GHz Bandwidth

This article presents a 16-GHz frequency-modulated continuous-waveform (FMCW) modulator for radar applications in 28-nm CMOS. A two-point modulation technique is applied to reach a fast-chirp operation. A digital-to-time converter (DTC)-based subsampling phase-locked loop (PLL) is implemented to eliminate the power and noise from the frequency divider. Compared with the conventional delta-sigma division ratio-modulated PLL, this article presents an FM modulator with a finer loop-time resolution that lowers the quantization noise and improves the chirp FM accuracy. A voltage-driven analog varactor enables a programmable chirp bandwidth up to 1.5 GHz. The frequency-digital to analog converter (FDAC) nonlinearity is pre-distorted by an on-chip calibration engine. This FMCW modulator chirps 1.5-GHz bandwidth within 10 μs. The corresponding root-mean-square (rms) frequency error is 230 kHz, which is less than 0.015% of the chirp bandwidth.

Enhanced Detection of Doppler-Spread Targets for FMCW Radar

Frequency-modulated continuous waveform signals are of great interest in automotive radar, perimeter radar, and wide-area surveillance radar applications. For automotive radars and wide-area surveillance radars, which generally utilize high Doppler frequency resolution for target recognition, the important potential target such as a walking person cannot be viewed as a point-like target due to different velocities of the reflection points of a pedestrian. The echoes of such targets have extended Doppler spectrum, and they appear as horizontal lines in the range-Doppler plane, rather than a single point considered in the traditional cases. However, the existing approaches do not make full use of the Doppler-spread characteristic to enhance the detection performance of pedestrians. In this paper, we will show how this characteristic can be used to enhance the detection performance for Doppler-spread targets. The main goal of this paper is pedestrian detection in wide-surveillance radar applications and the proposed approach can also be applied in automotive radar applications. Motivated by the Hough transform, the energies of most Doppler bins corresponding to the target will be accumulated to enhance the detection performance. The questions of how many and which cells should be accumulated in practical applications are discussed in detail. The proposed approach is based on the ordered statistical-constant false alarm rate but tailored to Doppler-spread targets. The detection performance of this algorithm is derived analytically, and verified via practical wide-area surveillance radar signals.

Serial‐fed linear frequency diverse arrays for obtaining direction of arrival (DOA) of frequency modulated continuous waveform (FMCW) sources with ambiguity reduction

Possibility of exploiting serial-fed linear arrays for obtaining the direction of arrival (DOA) of frequency modulated continuous waveform (FMCW) sources is discussed in this article. The angle of incident wave is assumed to be in the range, [−90°, 90°], with ambiguity reduction compared with the previous work. At first, the serial-fed arrays are assumed as a transmitter with triangular FMCW sources, composing modified frequency diverse arrays. An explicit angle dependency is obtained on the separations between the maximums of the produced spatial power pattern in a design procedure. The approach is generalized for modified sawtooth frequency modulated continuous waveform (SFMCW) sources, which are combinations of two SFMCW sources with two different slopes of frequency shifts. In addition, a measurement setup is implied assuming the serial-fed array as the receiver and an antenna with a known FMCW source and an unknown DOA as the transmitter. The DOA will be obtained from the separations between maxima of the received signals. Advantages of the proposed structure are the simplicity of antenna structure, ability of operation with narrowband antenna elements, and ambiguity reduction compared with the previous work.

Random phase code for automotive MIMO radars using combined frequency shift keying‐linear FMCW waveform

Automotive radar is a key component for self-driving cars and advanced driver assistant systems. The major requirements of recent automotive radars are high angular resolution and multiple target detection with the constraints of small size, low power, and low cost. With appropriate transmitter spacing, co-located multiple-input–multiple-output (MIMO) radar can emulate larger aperture arrays, producing the required high angular resolution. However, MIMO radar requires waveforms that are orthogonal in frequency, time, or code domain, and orthogonal waveforms developed for pulse radars are unsuitable for automotive frequency modulated continuous waveform (FMCW) radars. This study proposes a code division multiplexing method for automotive MIMO radars by selecting the combined frequency shift key-linear FMCW waveform. The authors show the performance through simulation and discuss constraints. The proposed method is suitable for automotive radars because not only can high angular resolution be achieved by a small number of arrays, but also multiple targets can be detected with the low sampling rate and computational power.

Estimation of Canopy Height Using an Airborne Ku-Band Frequency-Modulated Continuous Waveform Profiling Radar

An airborne Ku -band frequency-modulated continuous waveform (FMCW) profiling radar terms as Tomoradar provides a distance-resolved measure of microwave radiation backscattered from the canopy surface and the underlying ground. The Tomoradar waveform data are acquired in the southern Boreal Forest Zone with Scots pine, Norway spruce, and birch as major species in Finland. A weighted filtering algorithm based on statistical properties of noise is designed to process the original waveform. In addition, another algorithm of estimating canopy height for the processed waveform is developed by extracting the canopy top and ground position. A higher-precision reference data from a Velodyne VLP-16 laser scanner and a digital terrain model are introduced to validate the accuracy of extracted canopy height. According to the processed results from 127 765 copolarization measurements in 32 stripes of Tomoradar field test, the mean error of canopy height varies from −0.04 to 1.53 m, and the root-mean-square error approximates 1 m. Moreover, the estimated canopy heights highly correlate with the reference data in view of that the correlation coefficients maintain from 0.86 to 0.99 with an average value of 0.96. All these results demonstrate that Tomoradar presents an important approach in estimating the canopy height with several meters footprint and is feasible of being a validation instrument for satellite LiDAR with large footprint in the forest inventory.

The Comparison of Canopy Height Profiles Extracted from Ku-band Profile Radar Waveforms and LiDAR Data

An airborne Ku-band frequency-modulated continuous waveform (FM-CW) profiling radar, Tomoradar, records the backscatter signal from the canopy surface and the underlying ground in the southern boreal forest zone of Finland. The recorded waveforms are transformed into canopy height profiles (CHP) with a similar methodology utilized in large-footprint light detection and ranging (LiDAR). The point cloud data simultaneously collected by a Velodyne® VLP-16 LiDAR on-board the same platform represent the frequency of discrete returns, which are also applied to the extraction of the CHP by calculating the gap probability and incremental distribution. To thoroughly explore the relationships of the CHP derived from Tomoradar waveforms and LiDAR data we utilized the effective waveforms of one-stripe field measurements and comparison them with four indicators, including the correlation coefficient, the root-mean-square error (RMSE) of the difference, and the coefficient of determination and the RMSE of residuals of linear regression. By setting the Tomoradar footprint as 20 degrees to contain over 95% of the transmitting energy of the main lobe, the results show that 88.17% of the CHPs derived from Tomoradar waveforms correlated well with those from the LiDAR data; 98% of the RMSEs of the difference ranged between 0.002 and 0.01; 79.89% of the coefficients of determination were larger than 0.5; and 98.89% of the RMSEs of the residuals ranged from 0.001 to 0.01. Based on the investigations, we discovered that the locations of the greatest CHP derived from the Tomoradar were obviously deeper than those from the LiDAR, which indicated that the Tomoradar microwave signal had a stronger penetration capability than the LiDAR signal. Meanwhile, there are smaller differences (the average RMSEs of differences is only 0.0042 when the total canopy closure is less than 0.5) and better linear regression results in an area with a relatively open canopy than with a denser canopy.

3D-Subspace-Based Auto-Paired Azimuth Angle, Elevation Angle, and Range Estimation for 24G FMCW Radar with an L-Shaped Array.

In this paper, a three-dimensional (3D)-subspace-based azimuth angle, elevation angle, and range estimation method with auto-pairing is proposed for frequency-modulated continuous waveform (FMCW) radar with an L-shaped array. The proposed method is designed to exploit the 3D shift-invariant structure of the stacked Hankel snapshot matrix for auto-paired azimuth angle, elevation angle, and range estimation. The effectiveness of the proposed method is verified through a variety of experiments conducted in a chamber. For the realization of the proposed method, K-band FMCW radar is implemented with an L-shaped antenna.

Estimating Ground Level and Canopy Top Elevation With Airborne Microwave Profiling Radar

This paper presents the estimation of the ground elevation and canopy top elevation from the data collected by an airborne frequency-modulated continuous waveform profiling radar, Tomoradar. The estimated ground and canopy top elevations are critical for the derivation of reference information for the satellite-borne microwave radar data and the modeling of interaction between microwave radar signal and foliage. The methods of estimating the ground elevation and canopy top elevation from profiling radar are introduced, and the accuracy was evaluated via digital terrain model and Velodyne VLP-16 LiDAR integrated with the Tomoradar. To our knowledge, the ranging radar and the LiDAR data were simultaneously collected for the first time. The evaluation proved that the root-mean-square error (RMSE) of ground level estimation of the developed profiling radar can reach up to 0.33 m. When comparing the estimated canopy top peak elevation between the profile radar data and the LiDAR data, it was found that the side lobes of Tomoradar antenna system may produce undesired canopy backscatters when the size of the canopy gap is comparable to the footprint size of the main lobe, resulting in a higher canopy top elevation measurement from Tomoradar than that from LiDAR. The RMSE of the estimated canopy top peak elevation between two data sets was 0.32 m in the best case and 0.852 m on average. Moreover, the RMSE of point-to-point comparing the entire canopy tops elevation estimated from the data of two active remote sensing systems is 0.799 m after excluding the outliers.

Synthesis of Serial-Fed Frequency Diverse Arrays With Periodic Triangular Frequency-Modulated Continuous Waveform

Application of serial-fed arrays as the possible candidates for frequency diverse arrays (FDAs) is discussed in this letter. Periodic sawtooth frequency-modulated continuous waveform and triangular frequency-modulated continuous waveform (TFMCW) sources are considered as the input signals. Effects of periodic functions for the frequencies of input signal are indicated on the spatial patterns compared with common FDA with increasing and decreasing frequencies of elements. A measurement setup is proposed for the serial-fed FDA with periodic TFMCW sources. Expected receiving signals at different angles are also illustrated based on spatial power patterns for TFMCW FDA. It is indicated that distances between the maximums of the received signal are changing as the functions of angle.

Inverse synthetic aperture LADAR demonstration: system structure, imaging processing, and experiment result.

A long-distance inverse synthetic aperture LADAR (ISAL) imaging experiment outdoors over 1km for cooperative targets is demonstrated, which gets a two-dimensional high-resolution image with resolution exceeding 2.5cm. The system utilizes an electro-optic in-phase and quadrature modulator to output a linear frequency-modulated continuous waveform (LFMCW) with a bandwidth of 6GHz and pulse repetition frequency (PRF) of 16.7KHz. For the problem of the coherence of the laser, the effects of the coherent processing interval (CPI) and time delay of the local oscillator (LO) on the coherence are discussed. The fiber delay line is set and the CPI is reduced to lower the requirement of the frequency stability of the laser source. The images are formed by two-dimensional Fourier transform and joint time-frequency transform methods, respectively. In this paper, we present the system structure, imaging processing, and the experiment result in detail. The experiment result validates the performance of our system for ISAL imaging.

A 24 GHz dual FMCW radar to improve target detection for automotive radar applications

A 24 GHz automotive radar with dual frequency modulated continuous waveform (FMCW) is proposed. By using this modulation waveform, the ghost targets can be avoided, especially in multi-target situations. Thus, the detection ability of radar systems can be significantly improved. In this paper, in order to generate the dual FMCW signal, a dual FMCW modulation control logic (DFMCL) is proposed. This block incorporates a 24 GHz fractional-N phase locked loop (PLL), synthesise 24 GHz modulation waveform. The proposed architecture was designed using 130 nm CMOS process. Two alternative chirps of 12 ms and 6 ms were generated in the coherent processing interval. The modulation bandwidth was 200 MHz. Moreover, a radar transceiver, which consists of 24 GHz dual FMCW generator and monolithic microwave integrated circuits (MMICs), was accomplished. A behavioural simulation was conducted to evaluate the operation of the proposed generator. Then, the transceiver was modelled for testing the detection ability of the automotive radar. The results demonstrated that the proposed scheme has the ability to realise the Dual FMCW waveform for automotive radar systems. Furthermore, the system can avoid the ghost targets in multi-target scenarios.

FMCW Signal Detection and Parameter Extraction by Cross Wigner–Hough Transform

The combination of Wigner–Ville distribution (WVD) and Hough transform (HT) has been successfully used in detection and parameter extraction of frequency modulated continuous waveform (FMCW) signals. In this paper, a combination of Cross–Wigner–Ville and HT [(Cross Wigner–Hough transform (XWHT)] is proposed for detection and parameter extraction of FMCW signals with a novel methodology. The XWHT method makes use of the cross-terms created by WVD instead of trying to suppress them. Utilization of the properties of the cross-terms to detect and unveil the parameters of FMCW signals on HT space is a new approach. The performance of the method is compared with other Wigner–Hough transform-based methods in terms of transform speed, parameter extraction, and detection performance. As a result, this study proposes that the XWHT is a candidate method to be used in digital electronic support receivers’ automatic signal detection and analysis capabilities due to its speed and performance.

고해상도 주파수 추정 기법을 통한 차량용 레이더 시스템의 간섭 완화에 관한 연구

With the increased demand for automotive radar systems, mutual interference between vehicles has become a crucial issue that must be resolved to ensure better automotive safety. Mutual interference between frequency modulated continuous waveform (FMCW) radar system appears in the form of increased noise levels in the frequency domain and results in a failure to separate the target object from interferers. The traditional fast fourier transform (FFT) algorithm, which is used to estimate the beat frequency, is vulnerable in interference-limited automotive radar environments. In order to overcome this drawback, we propose a high-resolution frequency estimation technique for use in interference environments. To verify the performance of the proposed algorithms, a 77GHz FMCW radar system is considered. The proposed method employs a high-resolution algorithm, specially the multiple signal classification and estimation of signal parameters via rotational invariance techniques, which are able to estimate beat frequency accurately.

Low-Complexity Range-Azimuth FMCW Radar Sensor Using Joint Angle and Delay Estimation Without SVD and EVD

A low complexity range-azimuth frequency-modulated continuous-waveform (FMCW) radar sensor using joint angle and delay estimation method without singular value decomposition (SVD) and eigenvalue decomposition (EVD) is presented in this paper. Conventional joint angle and delay estimation techniques exploit the dual-shift-invariant structure of received signals through matrix decompositions, such as SVD and EVD, which increases the computational burden. The proposed method utilizes the dual-shift-invariant structure through matrix inversion and performs angle and delay estimation using extended one-dimensional pseudospectrum searching instead of two-dimensional pseudospectrum searching to reduce the computational complexity. We demonstrate the effectiveness of the proposed method through Monte-Carlo simulations. The proposed algorithm is also verified by processing real FMCW data collected in an anechoic chamber.

Analysis of Low Probability of Intercept Radar Signals Using the Reassignment Method

Digital intercept receivers are currently moving towards classical time-frequency analysis techniques for analyzing low probability of intercept radar signals. Although these techniques are an improvement over existing Fourier-based techniques, they still suffer from a lack of readability, due to poor time-frequency localization and cross-term interference, which may lead to inaccurate detection and parameter extraction. In this study, the reassignment method, because of its ability to smooth out cross-term interference and improve time-frequency localization, is proposed as an improved signal analysis technique to address these deficiencies. Simulations are presented that compare time-frequency representations of the classical time-frequency techniques with those of the reassignment method. Four different low probability of intercept waveforms are analyzed (two frequency modulated continuous wave waveforms and two frequency shift keying waveforms). The following metrics are used for analysis evaluation: Percent detection, number of cross-term false positives, lowest signal-to-noise ratio for signal detection, processing time, percent error of: Carrier frequency, modulation bandwidth, modulation period, time-frequency localization (x and y direction) and chirp rate. Experimental results demonstrate that the ‘squeezing’ and ‘smoothing’ qualities of the reassignment method improve readability over the classical time-frequency analysis techniques and consequently, provide more accurate signal detection and parameter extraction in all but one of the metrics categories.

High-Frequency Radar Cross Section of the Ocean Surface for an FMCW Waveform

The first- and second-order monostatic cross sections of the ocean surface in the context of high-frequency ground wave radar operation are derived for a dipole source with a linear frequency-modulated continuous waveform. The Fourier coefficients of the rough ocean surface are described as zero-mean Gaussian random variables. The electric field equations for the reception of vertically polarized radiation scattered from the ocean surface are obtained. The range spectra are calculated by Fourier transforming the received signal within the sweep interval. Fourier transformation of the autocorrelations of the electric fields received from the time-varying surface gives the Doppler spectra (power spectral densities). The cross sections are obtained by direct comparison of the spectral results with the monostatic radar range equation.

Mapping the Underworld – State-of-the-art review

A major UK initiative, entitled Mapping the Underworld (MTU), is seeking to address the serious social, environmental and economic consequences arising from an inability to locate accurately and completely the buried utility service infrastructure without resorting to excavations. One of the four MTU projects aims to develop and prove the efficacy of a multi-sensor device for accurate remote buried utility service detection, location and, where possible, utility identification. This paper aims to introduce the MTU programme followed by a state-of-the-art review of the three essential technologies that are to be combined in the device – ground penetrating radar (GPR), low-frequency quasi-static electromagnetic fields and acoustics – and a summary of the influence of different soil types and states on the transmission of the various signals, and therefore how the techniques might be optimised from a knowledge of the ground instead of using very broad simplifying assumptions. The latest developments in impulse GPR, frequency modulated continuous waveform (FMCW) GPR and stepped frequency continuous waveform (SFCW) GPR are described and previous attempts to combine GPR with other sensing technologies are introduced. The work on quasi-static fields explores the ‘fields-of-opportunity’ related to the 50 Hz currents flowing in existing underground power circuits and the electric field variations when low-frequency current in actively induced into the ground. Acoustic techniques have been primarily used for leak detection and the review focuses on the potential for their application to buried utility service location. The paper concludes with a discussion of the facilities required, and currently available, for comprehensive assessment and independent verification of the performance of both existing devices/technologies and of the multi-sensor device under development.