Stepped Frequency Continuous Wave Research Articles

Through-Wall Radar Classification of Human Posture Using Convolutional Neural Networks

Through-wall detection and classification are highly desirable for surveillance, security, and military applications in areas that cannot be sensed using conventional measures. In the domain of these applications, a key challenge is an ability not only to sense the presence of individuals behind the wall but also to classify their actions and postures. Researchers have applied ultrawideband (UWB) radars to penetrate wall materials and make intelligent decisions about the contents of rooms and buildings. As a form of UWB radar, stepped frequency continuous wave (SFCW) radars have been preferred due to their advantages. On the other hand, the success of classification with deep learning methods in different problems is remarkable. Since the radar signals contain valuable information about the objects behind the wall, the use of deep learning techniques for classification purposes will give a different direction to the research. This paper focuses on the classification of the human posture behind the wall using through-wall radar signals and a convolutional neural network (CNN). The SFCW radar is used to collect radar signals reflected from the human target behind the wall. These signals are employed to classify the presence of the human and the human posture whether he/she is standing or sitting by using CNN. The proposed approach achieves remarkable and successful results without the need for detailed preprocessing operations and long-term data used in the traditional approaches.

A Doppler Range Compensation for Step-Frequency Continuous-Wave Radar for Detecting Small UAV.

Step-frequency continuous-wave (SFCW) modulation can have a role in the detection of small unmanned aerial vehicles (UAV) at short range (less than 1–2 km). In this paper, the theory of SFCW range detection is reviewed, and a specific method for correcting the possible range shift due to the Doppler effect is devised. The proposed method was tested in a controlled experimental set-up, where a free-falling target (i.e., a corner reflector) was correctly detected by an SFCW radar. This method was finally applied in field for short-range detection of a small UAV.

An Improved Modified Universal Ultra-Wideband Antenna Designed for Step Frequency Continuous Wave Ground Penetrating Radar System.

Step Frequency Continuous Wave Ground Penetrating Radar (SFCW-GPR), as a tool for nondestructive testing of shallow soil surface targets, the realization of the function of SFCW-GPR is mainly based on the theory of refraction, reflection and scattering of electromagnetic wave in the discontinuity of dielectric constant. So, the UWB antenna system, an important part of SFCW-GPR, becomes more indispensable. In this paper, an improved modified universal antenna is designed, simulated and fabricated. Based on a typical Bow-tie antenna, it is modified by the methods of lumped loads, cavity-backed loading and structure loading. The simulated and measured results show that the UWB antenna has 1.36 GHz bandwidth from 0.64 to 2.0 GHz with three resonant wavelength peaks, and having been modified and improved, the UWB antenna performances including voltage standing-wave ratio (VSWR), input impedance, the boresight gain and current distribution, are much better than the typical Bow-tie antenna. In addition, the results of verification experiment of Step Frequency Continuous Wave (SFCW) show that the antenna can be applied to the working scenarios of SFCW-GPR.

A Comparative Analysis of Deterministic Detection and Estimation Techniques for MIMO SFCW Radars

In this paper, the problem of the joint estimation of the range and azimuth of multiple targets in a multiple-input multiple-output stepped-frequency continuous wave radar system is investigated. Three deterministic algorithms solving it through an iterative beam cancellation procedure are described; moreover, an iterative technique, based on the expectation-maximization algorithm, is developed with the aim of refining their estimates. The accuracy achieved by all the considered algorithms is assessed on the basis of the raw data acquired from a low power wideband radar device. Our results evidence that these algorithms achieve similar accuracies, but at the price of different computational efforts.

A Novel Method for Breath Detection via Stepped-Frequency Continuous Wave Ultra-Wideband (SFCW UWB) Radars Based on Operational Bandwidth Segmentation.

Human being detection via ultra-wideband (UWB) radars has shown great prospects in many areas, such as biomedicine, military operation, public security, emergency rescue, and so on. When a person stays stationary, the main feature that separates him/her from surroundings is the movement of chest wall due to breath. There have been many algorithms developed for breath detection while using UWB radars. However, those algorithms were almost based on a basic scheme that focused on processing in the time dimension of UWB data. They did not utilize the benefits from the wide operational bandwidth of UWB radars to show potential superiority over those narrowband systems such as a continuous wave (CW) Doppler radar. In this paper, a breath detection method was proposed based on operational bandwidth segmentation. A basic theoretical model was firstly introduced, indicating that characteristics of breath signals contained in UWB echoes were consistent among the operational frequencies, while those of clutters were not. So, the method divided a set of UWB echo data into a number of subsets, each of which corresponded to a sub-band within the operational bandwidth of the UWB radar. Thus information about the operational frequency is provided for subsequent processing. With the aid of the information, a breath enhancement algorithm was developed mainly by averaging the segmented UWB data along the operational frequency. The algorithm’s performance was verified by data measured by a stepped-frequency CW (SFCW) UWB radar. The experimental results showed that the algorithm performed better than that without the segmentation. They also showed its feasibility for fast detection of breath based on a short duration of data. Moreover, the method’s potential for target identification and impulse-radio (IR) UWB radar was investigated. In summary, the method provides a new processing scheme for UWB radars when they are used for breath detection. With this scheme, the UWB radars have a benefit of greater flexibility in data processing over those narrowband radars, and thus will perform more effectively and efficiently in practical applications.

An autofocusing method for imaging the targets for TWI radar systems with correction of thickness and dielectric constant of wall

AbstractIn through the wall imaging systems, wall parameters like its thickness and dielectric constant play an important role in the true and correct image formation of an object behind the wall made of various materials like brick cement, wood, plastic, etc. Incorrect estimation of these parameters leads to dislocation of the object and smearing or blurriness of the image too. A new autofocusing technique for a stepped frequency continuous wave -based radar at the frequency of 1–3 Ghz has been developed that corrects the wall's parameters like its thickness and dielectric constant and provides a better focused image of the target. For this purpose, a peak signal to noise ratio -based autofocusing technique has been developed by using curve fitting and the genetic algorithm. It is observed that the proposed technique has capability to focus the image up to good extent.

Near Range Radar Imaging Based on Block Sparsity and Cross-Correlation Fusion Algorithm

In this paper, we propose a novel processing model for compressive sensing (CS)-based stepped-frequency continuous-wave (SFCW) radar near range imaging, which takes the azimuth dependence of the reflection coefficients of targets into consideration. Based on the block sparse property of the received signal in the defined dictionary, 2-D images of the targets can be obtained at each spatial sampling point. A cross-correlation method is then employed to fuse these 2-D images to obtain the final result. Random undersamplings of frequencies and spatial sampling points are conducted to reduce the data acquisition time, the data size, and the computational complexity. Experimental results of an SFCW-based MIMO radar and a ground-based SAR system show that, compared with the conventional matched filtering-based methods, the proposed method can provide artifacts-reduced higher resolution images by using reduced frequencies and spatial sampling points. We also demonstrate that, compared to the conventional CS-based methods, due to the more suitable established observation model, the proposed method can achieve better imaging results with fewer artifacts for near range targets.

Method for Compensating Signal Attenuation Using Stepped-Frequency Ground Penetrating Radar.

Ground penetrating radar (GPR) is a subsurface remote sensor that allows the user to detect, classify, and identify the buried target and structures. The radar signals are rapidly attenuated as they propagate into the ground; therefore, attenuation compensation is necessary for the visualization of the buried targets from GPR data. In this work, we developed a novel attenuation compensation approach based on the recently developed stepped-frequency continuous wave (SFCW) GPR system, which is a frequency domain sampling system with improved performance in dynamic range, sensitivity, and anti-interference ability. Because the regularly used time-varying gain function for compensating the attenuation of impulse GPR data does not make full use of the advancement of the SFCW modulation, an alternative procedure is proposed herein. The new approach is based the SFCW mechanism, and aims at improving the visualization of deeper targets by compensating the SFCW GPR signal attenuation. We first present the attenuation mode of the SFCW GPR echo, from which an inverse attenuation function is derived to compensate the amplitude loss. For the field measurement where the theoretical inverse attenuation function is difficult to achieve, we introduced a pseudo time–frequency distribution for estimating the inverse attenuation function. A procedure for amplitude attenuation has also been developed. Testing with both synthetic and experimental data return a good reconstruction of the signal amplitude, subsequently improving the ability for visualizing and detecting deeper targets.

Reconstruction Algorithm of Compressed Sensing for Stepped-Frequency Continuous Wave Ground Penetrating Radar Based on Block Objects

Reconstruction Algorithm of Compressed Sensing for Stepped-Frequency Continuous Wave Ground Penetrating Radar Based on Block Objects

Photonics-Based Dual-Band Radar for Landslides Monitoring in Presence of Multiple Scatterers

In this paper, a dual-band photonics-based radar system used for precise displacement measures in a multitarget scenario is described. The radar was designed for monitoring applications to prevent both structural failures of buildings and landslides. The radar system exploits the technique of stepped frequency continuous wave signal modulation and the displacement of the targets is evaluated through differential phase measurements. In this work, encouraged by the results already achieved in the single-target scenario, we present an investigation extended to the case of multiple targets. We aim to evaluate the accuracy of the displacement estimation both from a simulated and experimental point of view, and to understand how multiple targets impact on the final estimate of displacements. Simulation results demonstrate that it is possible to achieve a typical accuracy of less than 0.2 mm for distances up to 400 m. These results are confirmed by preliminary experimental outcomes, which take into account different operative conditions with multiple targets. Finally, concluding remarks and perspectives draw the agenda for our future investigations.

Effect of ground undulation and mounted vehicle velocity variation on stepped frequency continuous wave GPR data

This paper describes a method to generate dataset on stepped frequency continuous wave (SFCW) ground penetrating radar (GPR) for land mine detection. Probability of target detection as well as accuracy of GPR is hindered by ground undulations and GPR mounted vehicle velocity variation. This paper proposes a novel method of filtering out ground undulation effect by ground bounce removal filter and also mitigating GPR mounted vehicle velocity variations. This work also focuses on migration of simulated B-scan and C-scan data using Kirchhoff and F-K migration algorithms. The irregular surface condition of the ground or ground undulation is modelled and a ground bounce removal filter is developed to eliminate the effects of ground undulation. Non-uniform sampling of B-scan replicates the scenario of variation in velocity of the GPR mounted vehicle. The Kirchhoff and F-K migration algorithms applied to the outcome of ground bounce removal filter dataset results in no/less error with respect to true depth and position of the landmine in all possible scenarios. An interactive graphical user interface (GUI) for generating and testing the SFCW GPR data is also discussed in this paper.

Comparison of digital beamforming algorithms for 3-D terahertz imaging with sparse multistatic line arrays

Abstract. In this contribution we compare the back-projection algorithm with our recently developed modified range migration algorithm for 3-D terahertz imaging using sparse multistatic line arrays. A 2-D planar sampling scheme is generated using the array's aperture in combination with an orthogonal synthetic aperture obtained through linear movement of the object under test. A stepped frequency continuous wave signal modulation is used for range focusing. Comparisons of the focusing quality show that results using the modified range migration algorithm reflect these of the back-projection algorithm except for some degradation along the array's axis due to the operation in the array's near-field. Nevertheless the highest computational efficiency is obtained from the modified range migration algorithm, which is better than the numerically optimized version of the back-projection algorithm. Measurements have been performed by using an imaging system operating in the W frequency band to verify the theoretical results.

Algorithm to process the stepped frequency radar signal for a thin road surface application

This article describes an algorithm for calculating the relative permittivity from a stepped frequency continuous wave radar (SFCW) signal. The intended application for the developed radar is a quality estimation of the road surface layer, which includes homogeneity and density estimation. Automated fast computations are needed for road surveying purposes, which must be conducted alongside the normal traffic and with typical traffic speeds. For SFCW, we get N sweep waveforms for each sample point, where N equals the number of frequency steps, which poses a computational problem for onboard data acquisition. Radar signal processing steps are at first conducted in the frequency domain, where initial calibration corrections are applied. This data is then transferred to the time domain via inverse Discrete Fourier Transform. The relative permittivity is calculated from the peak produced by the surface reflection. A proof of the concept is given in the form of a pilot measurement on a real road. Results indicate that the automated signal detection algorithm is accurate enough to be used in real life measurements.

Signal processing for coal layer thickness estimation using high‐resolution time delay estimation methods

The coal mining research technology is gaining popularity in terms of thickness measurement of coal mining horizon. The main challenge is to improve a robust sensing method for estimating the coal layer thickness left on mine-haulage way roofs for mine safety. This study addresses this challenge by step frequency continuous wave ground penetrating radar (GPR), whose resolution is dependent on bandwidth. To improve the time resolution of GPR signal, this study adopted four high-resolution algorithms, which are also known as subspace methods, namely, estimation of signal parameter via rotational invariance techniques, multiple-signal classification (MUSIC) algorithm, polynomial version of MUSIC, i.e. root-MUSIC and root-Min-Norm. The performance of all these algorithms is compared with synthetic data generated by the plane wave model and full wave model. The results are presented in terms of resolution power as well as relative root-mean-square error on the estimated thickness.

Stepped Frequency Continuous Wave Ground Penetrating Radar Imaging Algorithm Based on Multi-task Bayesian Compressive Sensing

Aiming at the joint sparsity of target imaging space of SFCW-GPR, the idea of multi-task learning is introduced into the Bayesian compressive sensing reconstruction algorithm, multi-task Bayesian compressive sensing(MT-BCS) algorithm is proposed in the paper. A common prior hierarchical Bayesian model is used for different tasks, MT-BCS algorithm can fully exploit the statistical characteristics and structural information of radar echo data and recover original signals from far fewer random samples. The simulation results show that the reconstruction accuracy of MT-BCS algorithm is better than BCS algorithm under the same conditions.

Step frequency continuous wave RADAR sensor for level measurement of molten solids

Step frequency continuous wave (SFCW) RAdio Detection And Ranging (RADAR) sensor is proposed for non-contact measurement of the absolute level of molten solids in industrial furnaces. A conical horn is optimized for operation over 10–16 GHz in mono-static configuration for level measurement. The absolute distance of a stationary target was measured with 3 mm accuracy using the SFCW RADAR sensor in mono-static mode. Stable measurements were recorded for 4.35 h in a furnace at 450 °C. Level measurements of molten glass and aluminum in 1100 °C furnace indicate the feasibility of industrial-level gauging.

Comparison Study of Noncontact Vital Signs Detection Using a Doppler Stepped-Frequency Continuous-Wave Radar and Camera-Based Imaging Photoplethysmography

In this paper, we compare the performance of radar and optical (camera based) techniques in detecting vital signs such as respiratory rate (RR), heart rate (HR), and blood oxygen saturation (SpO2). Specifically, we investigate the application of ultrawideband stepped-frequency continuous-wave radar and imaging photoplethysmography (iPPG) techniques to measure vital signs. The radar performance can be enhanced by using phase information of backscattered signal instead of its amplitude. On the other hand, the iPPG system can be enhanced by using more than one camera and utilizing very selective narrowband filters coupled with good illumination. In either system, use of advanced signal processing is required to improve accuracy. Generally, HR and RR can be accurately read by either microwave radar or optical techniques with 500 lx illumination level to have < ±2% error up to 2 m distance between the subject and the system, but optical technique errors increase significantly to < ±15% for <200 lx. However, each system has its unique advantages as the radar can be used for seeing-through walls and optical technique is uniquely capable of measuring SpO2).

Bitstream radar waveforms for generic single-chip radar

Bitstreams, square wave digital signals, enable flexible radar implementations in modern digital technology. By using bitstreams in place of analog sinusoidal waveforms, we can realize continuous-wave (CW), stepped-frequency CW, frequency-modulated CW, or even pseudo random noise-sequence and pulsed radars, all with a single bit of amplitude resolution. The building blocks are a programable waveform generator, a sweep threshold quantizer, digital delay, and a digital XOR gate as a mixer. This gives us a novel, almost fully digital (requiring only a comparator) system, as previously proposed and which is extended here. The flexibility of the transmitter allows for easy switching between waveforms and the bitstream signal can be processed with single-bit digital gates. Single-bit signals allows for exploration of novel continuous time non-clocked digital implementations to maximize speed and energy efficiency. Mixing frequencies with a digital XOR gate creates harmonics, which are explored for multiple solutions utilizing digital delay. Analytical as well as simulation results are presented. Initial measurements from a 90 nm CMOS chip is provided for the transmitter and the full system, proving the feasibility of a digital future in radar.

Monostatic continuous-wave radar integrating a tunable wideband leakage canceler for indoor tagless localization

Continuous-wave (CW) radars have been recently investigated in healthcare aiming at contactless health monitoring. However, a major problem in monostatic CW architectures is represented by the unwanted leakage produced by poor isolation between transmitter and receiver, which can drastically decrease the receiver's sensitivity reducing therefore the radar dynamic range. Although this situation can be easily controlled in case of narrowband CW radar by an appropriate passive microwave design, it becomes much more complicated in case of stepped-frequency CW and frequency-modulated CW architectures that present an ultra-wideband nature. In this paper, a monostatic CW radar integrating a tunable wideband leakage canceler aiming at indoor tagless localization is presented and discussed. The use of the feedforward canceler allows a strong reduction of the unwanted leakage over the whole radar bandwidth. Experimental results demonstrate the feasibility of this approach, showing an outstanding improvement of the radar dynamic range.

Short-Range Imaging System With a Nonuniform SFCW Approach

Stepped-frequency continuous-wave (SFCW) radar systems with real-time capability can utilize only a moderate number of frequency points to achieve a high sweep rate. Thus, range ambiguities of clutter become crucial because of a possible obscuration of the target response. An optimized nonuniform SFCW concept is introduced to reduce the maximum ambiguity level. This nonuniform frequency sweep is applied to an active multistatic imaging system for personnel screening. The sweep design improves the system’s robustness against clutter due to reflections from surrounding objects outside the ambiguity-free imaging area of the system. This paper extends the prior work with an analytical approach to estimate the maximum ambiguity level, which is important for the design of an appropriate frequency sweep. Based on the analytical work, an optimum sweep design is proposed and verified with simulation and experimental results. Measurements are conducted with bi- and multistatic radar setups.