Doppler Information Research Articles

FREQUENCY RESPONSE OF UWB SIGNAL IN A BEATING HEART

The measurement, monitoring of heartbeat and its rate are necessary to know the health of the heart of human beings. In addition, they are needed for extended applications like criminal investigation, law enforcement, defense and military usage, search, rescue operation, etc. The ultra-wideband (UWB) radars found growing interest in recent years as they are able to overcome the limitations of continuous-wave (CW) Doppler radars in detecting human heartbeat. Modeling and analysis of the UWB pulse propagation behavior through a human body is important before developing a practical UWB radar. Several researchers have estimated the reflected signals to study if their variations correlate with the heartbeat rate. However, the reflected signal strength carrying Doppler information received at the radar after a two-way propagation of the RF signal was found to be too weak for detection. This paper presents (i) a model for UWB wave propagation through a human thorax and (ii) estimation via simulation, of transmission coefficient at various frequencies in the UWB range 1–10[Formula: see text]GHz using CST Microwave Studio. The study clearly indicates that the variation of power transmission coefficient of UWB signal has a strong correlation to the instantaneous dimension of the heart in a cardiac cycle, a feature that can be exploited in detecting cardiac activity of human being using radar-based principles.

H-scan Subtraction Doppler Imaging: A Novel Ultrasound Small Blood Vessel Flow Characterization with Scattering and Reflection Identification

Ultrafast compound Doppler imaging (UCDI), which can be used to acquire Doppler information at very high spatial and temporal sampling rates, provides a great improvement to the characterization of the vasculature. The singular value decomposition (SVD) technique takes advantage of the different features of tissue and blood motion in terms of spatiotemporal coherence and strongly outperforms conventional clutter rejection filters in small animals. However, a major challenge of conventional UCDI with SVD clutter filtering for small vessel imaging is that it is not sensitive enough to detect the hemodynamic changes in deep tissue where the majority of the remaining signal is usually noise-saturated. In this study, with the first attempt to apply ultrasonic tissue characterization techniques to UCDI, we propose an H-scan subtraction Doppler imaging method to bypass the limitations associated with the high-order singular value thresholding selection and improve the image quality of fine vessels. The flow phantom experiments with different blood concentrations show that H-Scan is capable of estimating the relative size and spatial distribution of acoustic scattering objects. In the in vivo rabbit brain experiment, the H-Doppler method, together with the global and block-wise local SVD clutter filtering, are proposed to facilitate better power Doppler images with a significant improvement of background noise suppression. These results demonstrate that the contrast-to-noise-ratio (CNR) of the H-scan subtraction Doppler imaging is 15% to 65% higher than that of the conventional UCDI methods. Therefore, this approach can be potentially applied to the clinical applications of the functional ultrasound (fUS) imaging method.

Novel DOAs estimation method based on Doppler aided Chinese remainder theorem with all phase DFT for multiple targets in sparse array

In this study, the authors take further insight into the sparse geometry which offers a larger array aperture than uniform linear array with the same number of physical sensors. A novel direction of arrivals (DOAs) estimation model with flexible sparse geometry, which possesses the potential to significantly improve the estimation performance especially when the placed space and the weight of carrier such as airborne radar are restricted, is proposed to offer a larger aperture compared with co-prime array. The proposed algorithm can estimate DOAs by solving phase ambiguity. To improve the capability of spectrum analysis in frequency domain, all phase discrete Fourier transform (DFT), which can effectively alleviate spectrum leakage compared with traditional DFT, is proposed to apply into DOAs estimation. Additionally, the performance on degrees of freedom can be considerably improved compared with the state of the art where all the targets can be distinguished by Doppler information of received echo signal. More importantly, the proposed algorithm can effectively deal with DOA-closely-spaced targets because the proposed algorithm does not require to estimate signal subspace with ill-conditioned steering matrices. Both the theoretical analysis and simulation results demonstrate that the proposed algorithm significantly improves DOAs estimation precision with less computation cost.

Passive WiFi Radar for Human Sensing Using a Stand-Alone Access Point

Human sensing using WiFi signal transmissions is attracting significant attention for future applications in e-healthcare, security, and the Internet of Things (IoT). The majority of WiFi sensing systems are based around processing of channel state information (CSI) data which originates from commodity WiFi access points (APs) that have been primed to transmit high data-rate signals with high repetition frequencies. However, in reality, WiFi APs do not transmit in such a continuous uninterrupted fashion, especially when there are no users on the communication network. To this end, we have developed a passive WiFi radar system for human sensing which exploits WiFi signals irrespective of whether the WiFi AP is transmitting continuous high data-rate Orthogonal Frequency-Division Multiplexing (OFDM) signals, or periodic WiFi beacon signals while in an idle status (no users on the WiFi network). In a data transmission phase, we employ the standard cross ambiguity function (CAF) processing to extract Doppler information relating to the target, while a modified version is used for lower data-rate signals. In addition, we investigate the utility of an external device that has been developed to stimulate idle WiFi APs to transmit usable signals without requiring any type of user authentication on the WiFi network. In this article, we present experimental data which verifies our proposed methods for using any type of signal transmission from a standalone WiFi device, and demonstrate the capability for human activity sensing.

Code Design for Moving Target-Detecting Radar in Nonhomogeneous Signal-Dependent Clutter

In this paper, we investigate the code design problem of improving the detection performance of a moving target in the presence of nonhomogeneous signal-dependent clutter for moving target-detecting (MTD) radar systems. The optimization metric is constructed based on the signal to clutter and noise ratio (SCNR) of interpulse matched filtering. Under the frameworks of cyclic and majorization-minimization algorithms, we propose a novel algorithm, named CMMCODE, to tackle the code design optimization problem in the case of unknown precise target Doppler information and nonhomogeneous clutter. In the white-noise case, the simplified algorithm is also given based on CMMCODE algorithm. The presented algorithm is computationally efficient and convergent. Numerical examples show the effectiveness of the proposed algorithms.

Doppler-aided positioning in GNSS receivers - A performance analysis

The main objective of Global Navigation Satellite Systems (GNSS) is to precisely locate a receiver based on the reception of radio-frequency waveforms broadcasted by a set of satellites. Given delayed and Doppler shifted replicas of the known transmitted signals, the most widespread approach consists in a two-step algorithm. First, the delays and Doppler shifts from each satellite are estimated independently, and subsequently the user position and velocity are computed as the solution to a Weighted Least Squares (WLS) problem. This second step conventionally uses only delay measurements to determine the user position, although Doppler is also informative. The goal of this paper is to provide simple and meaningful expressions of the positioning precision. These expressions are analysed with respect to the standard WLS algorithms, exploiting the Doppler information or not. We can then evaluate the performance improvement brought by a joint frequency and delay positioning procedure. Numerical simulations assess that using Doppler information is indeed effective when considering long observation times, and particularly useful in challenging scenarios such as urban canyons (constrained satellite visibility) or near indoor situations (weak signal conditions which need long integration times), thus providing new insights for the design of robust and high-sensitivity receivers.

Association between impedance to blood flow in umbilical arteries and infant survival in twin-to-twin transfusion syndrome.

To evaluate infant survival according to the Doppler pattern of impedance to blood flow in the umbilical arteries (UAs) prior to laser surgery, in pregnancies with twin-to-twin transfusion syndrome (TTTS). This was a retrospective study of women with a monochorionic diamniotic twin pregnancy who underwent laser surgery for TTTS between January 2012 and May 2018 at a single institution. Absolute intertwin difference in UA pulsatility index (DUAPI) was measured within 48 h prior to laser surgery. Twins with intermittent or persistent absent/reversed end-diastolic flow (EDF) in the UA (UA-EDF) were analyzed separately. Survival of both or at least one infant at birth and at 30 days postpartum was compared between pregnancies with an intertwin DUAPI of ≥ 0.4 and those with an intertwin DUAPI of < 0.4, as well as between fetuses with intermittent and those with persistent absent/reversed UA-EDF. Parametric and non-parametric tests were used for analysis. Regression analysis was performed to determine if intertwin DUAPI and intermittent or persistent absent/reversed UA-EDF were associated independently with infant survival, while controlling for gestational age at delivery, Quintero stage and other important confounding variables. Of 231 TTTS pregnancies that underwent laser surgery during the study period, UA Doppler information could be retrieved for 206 and delivery information was available for 184, which comprised the study population. Rates of double-twin survival at birth were significantly higher in pregnancies with an intertwin DUAPI of < 0.4 than in those with an intertwin DUAPI of ≥ 0.4 (83.9% (78/93) vs 50.0% (12/24); P < 0.001). Double-infant survival at birth was higher in pregnancies with intermittent compared to those with persistent absent/reversed UA-EDF (73.0% (27/37) vs 36.7% (11/30); P = 0.003). Regression analysis demonstrated that an intertwin DUAPI of < 0.4 was associated with increased survival of both twins at delivery (P < 0.001) and at 30 days postpartum (P = 0.002), as well as increased survival of at least one twin at delivery (P = 0.009). Similarly, intermittent absent/reversed UA-EDF was associated with increased survival of both twins at delivery (P = 0.007) and at 30 days after birth (P = 0.015). Evaluation of intertwin differences in UA impedance to blood flow as well as identification of intermittent or persistent absent or reversed UA-EDF prior to laser surgery could help in the prediction of double-infant survival at birth and to 30 days in twin pregnancies with TTTS. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Synthetic aperture processing for wireless communication signals with passive moving array

In this paper, we investigate the use of synthetic aperture technique in communication signal processing with passive moving arrays. First, demodulation preprocessing schemes proper to distinctive situations are provided to increase the coherence time of target signal. Then demodulated signal sequence is resampled and reconstructed for synthetic array data production. Secondly we consider the practical implementation of direction of arrival estimation and present approaches to adjust for synthetic array data. The proposed technique incorporates Doppler information caused by the moving of platform into spatial processing, leading to significant enhancement in achievable array performance. Both theoretical analysis and numerical simulations are presented to illustrate the effectiveness of the proposed methods.

레이다 모션에 따른 STAP 위상 보상

The conventional space-time adaptive processing (STAP) using a short coherent processing interval (CPI) is generally applied to an environment, where the variations in angle and Doppler information caused by stationary clutter patches during the CPI are negligible. The direct application of the conventional STAP to a relatively long CPI environment causes a performance degradation. This study proposes a method of applying the conventional STAP to the data acquired for a medium CPI scenario. In the proposed method, we compensate for the received signal phase by considering the change in the angle and Doppler information during the CPI, which results in the reduction of the phase variation due to the radar motion. Furthermore, we propose a method of improving the angular resolution by forming a virtual aperture when a high PRF radar with a non-negligible motion that satisfies the DPCA condition. Finally, we demonstrate the proposed method’s performance through a simulation.

Radial Velocity Photon Limits for the Dwarf Stars of Spectral Classes F–M

Abstract The determination of extrasolar planet masses with the radial velocity (RV) technique requires spectroscopic Doppler information from the planet’s host star, which varies with stellar brightness and temperature. We analyze the Doppler information in spectra from dwarfs of spectral types F–M utilizing empirical information from HARPS and CARMENES data and model spectra. We revisit the question of whether optical or near-infrared instruments are more efficient for RV observations in low-mass stars, and we come to the conclusion that an optical setup (BVR bands) is more efficient than a near-infrared one (YJHK) in dwarf stars hotter than 3200 K. We publish a catalog of 46,480 well-studied F–M dwarfs in the solar neighborhood, and we compare its distribution to more than 1 million stars from Gaia DR2. For all stars, we estimate the RV photon noise achievable in typical observations under the assumption of no activity jitter and slow rotation. We find that with an ESPRESSO-like instrument at an 8 m telescope, a photon noise limit of 10 cm s−1 or lower can be reached in more than 280 stars in a 5 minute observation. At 4 m telescopes, a photon noise limit of 1 m s−1 can be reached in a 10 minute exposure in approximately 10,000 predominantly Sun-like stars with a HARPS-like (optical) instrument. The same applies to ∼3000 stars for a red optical setup that covers the R and I bands and ∼700 stars for a near-infrared instrument. For the latter two, many of the targets are nearby M dwarfs. Finally, we identify targets in which Earth-mass planets within the liquid water habitable zone can cause RV amplitudes comparable to the RV photon noise. Assuming the same exposure times as above, we find that an ESPRESSO-like instrument can reach this limit for 1 M ⊕ planets in more than 1000 stars. The optical, red optical, and near-infrared configurations reach the limit for 2 M ⊕ planets in approximately 500, 700, and 200 stars, respectively. An online tool is provided to estimate the RV photon noise as a function of stellar temperature and brightness and wavelength coverage.

A double-threshold target detection method in detecting low slow small target

Abstract With the rapid development of Unmanned Aerial Vehicle (UAV), stealth warship and stealth tank, the mission of radar has become more difficult. The modern radar system must detect and track target through strong clutter from many aspect, such as ground and sea. Radar detection for low slow small （LSS）targets has gradually become a new focus. LSS target has a small Radar Cross Section (RCS) because of its small size, making the SNR of the echo signal very low. At the same time, the Doppler frequency of slow target is very low, making it difficult for conventional signal processing methods to separate the Doppler information from the clutter spectrum. Thus, it does make sense to study how to detect the LSS target in strong clutter efficiently. In this paper, the distribution characteristics of radar clutter and coherent accumulation algorithm for LSS target detection in complex electromagnetic environment are studied. On the base of that, a double-threshold target detection method based on coherent accumulation is proposed. To check out the efficiency of the detection method, an experiment has been conducted, and the data collected was used to test the detection algorithm, and the result has been shown in this paper.

Detecting Targets above the Earth’s Surface Using GNSS-R Delay Doppler Maps: Results from TDS-1

Global Navigation Satellite System (GNSS) reflected signals can be used to remotely sense the Earth’s surface, known as GNSS reflectometry (GNSS-R). The GNSS-R technique has been applied to numerous areas, such as the retrieval of wind speed, and the detection of Earth surface objects. This work proposes a new application of GNSS-R, namely to detect objects above the Earth’s surface, such as low Earth orbit (LEO) satellites. To discuss its feasibility, 14 delay Doppler maps (DDMs) are first presented which contain unusually bright reflected signals as delays shorter than the specular reflection point over the Earth’s surface. Then, seven possible causes of these anomalies are analysed, reaching the conclusion that the anomalies are likely due to the signals being reflected from objects above the Earth’s surface. Next, the positions of the objects are calculated using the delay and Doppler information, and an appropriate geometry assumption. After that, suspect satellite objects are searched in the satellite database from Union of Concerned Scientists (UCS). Finally, three objects have been found to match the delay and Doppler conditions. In the absence of other reasons for these anomalies, GNSS-R could potentially be used to detect some objects above the Earth’s surface.

Detection improvement of off-pin targets in FMCW radars

Frequency Modulated Continuous Wave (FMCW) radars get target range and Doppler information by extracting the target beat frequency and phase exchange based on the well-known Two-Dimensional Fast Fourier Transform (2D-FFT) processing algorithm. Target whose beat frequency does not lie on the FFT grids suffers from great detection degradation. Doubling the number of FFT points, and consequently, the hardware processing complexity is a common solution to solve this problem. In this paper, a proposed method to increase the detection performance of these targets and avoid increasing system complexity is introduced. The proposed method depends on applying a proposed filter following the first and second FFT algorithms. The filter order and weights are chosen so that only one peak form the adjacent peaks of off-pin targets are distinguished. The superiority of the proposed method over the traditional one is validated for different scenarios through the Receiver Operating Characteristic (ROC).

δ‐GLMB filter based on DI in a clutter

For the problem that the performance of existing multi-target tracking algorithm's serious degrades in a dense clutter environment, a novel Doppler information assistant δ-generalised labelled multi-Bernoulli (DI-δ-GLMB) filter is proposed. By introducing DI, a new measurement likelihood function is established, and the improved update equation based on the δ-GLMB filter framework is derived. In addition, a sequential Monte Carlo implementation method is given under the non-linear model. Simulation results show that compared with the DI probability hypothesis density filter and the standard δ-GLMB filter, the estimation of the proposed algorithm is more accurate and stable.

Improved multi‐target tracking algorithm based on SMC‐CBMeMBer for the airborne Doppler radar

To effectively suppress clutter in airborne Doppler radar and improve multi-target tracking (MTT) performance, this study proposes an improved MTT algorithm based on Sequential Monte Carlo Cardinality Balanced Multi-target Multi-Bernoulli (SMC-CBMeMBer) filter. Firstly, the filter introduces Doppler information in the measurement process. Then, the more accurate likelihood function and state estimation are deduced again in the filtering update stage. Finally, the influence of particles number on the algorithm is analysed. Through the simulation experiment, when the number of particles is selected properly, the algorithm can more effectively suppress the clutter and improve the target tracking performance.

Multi‐mode propagation mode localisation and spread‐Doppler clutter suppression method for multiple‐input multiple‐output over‐the‐horizon radar

Multi-mode spread-Doppler clutter (SDC), caused by a stratified ionosphere, affects the detection performance of over-the-horizon radar on slow ships. To improve a multiple-input multiple-output over-the-horizon radar (MIMO-OTHR) system's performance and to mitigate the lingering effect of SDC, a novel multi-mode SDC suppression method based on full-mode spatial separation is proposed here. Furthermore, authors' method can estimate the elevation angle of direction of departure (DOD) and direction of arrival (DOA), contributing to mode localisation. By applying the bi-orthogonality of matrices, the cost function of single-mode component analysis is constructed under a least square criterion. By iteratively solving for the cost function, and by applying a systematic multistage decomposition, the elevation DOD and DOA and the slow-time Doppler information of each mode are obtained sequentially. Compared with classical SOBI and SS-SOBI methods, the proposed method improves the output signal-to-clutter-plus-noise ratio for spatial filtering. The estimated DOD and DOA do not need to be paired, reducing the angle error inherent in the SR method while performing the transmit-receive cascade refinement searching step. Simulation results demonstrate the excellent performance of the proposed method, which is beneficial to improve the ability of MIMO-OTHR to detect slow ships and determine the propagation mode.

Beamspace MUSIC Algorithm based on Space-time Array Signal Model

This paper is devoted to the direction-of-arrival (DOA) algorithm in the moving array scenario. A beamspace MUSIC algorithm based on space-time signal model is proposed to cope with this scenario. First, the DOA information contained in Doppler shift is used to combine with the array spatial information, thus constructing a space-time signal model. Second, allowing for the considerable dimension and complexity of the space-time model, we transform the array sensor data into beamspace to reduce the computation load. The introduction of Doppler information leads to significant enhancement in algorithm performance. Simulation results demonstrate the promotion of proposed algorithm.

Labelled GM‐CBMEMBER filter with adaptive track initiation

The initial Gaussian mixture cardinality balanced multi-target multi-Bernoulli (GM-CBMeMBer) filter does not provide track information and assumes that the target birth intensity is known as a priori, but in reality the target may appear anywhere in the detection area. Therefore, the study proposes a labelled GM-CBMeMBer filter with adaptive track initiation. First, the filter introduces track label information and selects the measurements of newborn targets in the prediction process. In addition, it also makes full use of the Doppler information of the airborne Doppler radar. Then, the position estimate and velocity estimate of newborn targets are calculated by using position measurements converted and Doppler measurements, respectively. Further the label information in the prediction process is inherited during the update process, and the target states are updated sequentially with the Doppler measurements after having been updated by using position measurements. Monte–Carlo experiments show that the proposed filter can perform adaptive track initiation effectively, with good tracking performance, and provide target track information well.

Target Kinematic State Estimation With Passive Multistatic Radar

This article examines methods for and results of determining the instantaneous kinematic state of a target, i.e., its velocity and heading, using passive multistatic radar. This is achieved by combining bistatic target range and Doppler information obtained by multiple bistatic transmitter-receiver pairs, to estimate the appropriate target velocity vector. This estimation is provided as a set of closed-form equations, derived for a general case applicable to an arbitrary number of transmitters. The feasibility of the proposed approach and its accuracy predictions, as a function of the number of transmitters, are experimentally confirmed via a dedicated experimental campaign with Global Navigation Satellite Systems as transmitters of opportunity, where two different and relatively slow-moving maritime targets were in the field of view of up to 12 satellite transmitters belonging to different satellite constellations (GPS, GLONASS, and Galileo) simultaneously.

Through-Wall Remote Human Voice Recognition Using Doppler Radar With Transfer Learning

We investigated the feasibility of using Doppler radar to recognize human voices by capturing the micro-Doppler signatures of vibrations from the larynx and mouth. The signatures produced through the vibrations of a human being’s vocal cords generate unique micro-Doppler signatures, depending on the letters pronounced. These can then be used to classify and recognize different words and letters. In this paper, we could successfully capture echo signals using the Doppler radar when a human subject spoke seven musical notes from Do to Ti and alphabet letters from $\boldsymbol {A}$ to $\boldsymbol {Z}$ . Spectrogram analysis was conducted for classification purposes, and the deep convolutional neural networks employed could classify the 26 letters to an accuracy of 94%. To overcome the deficiency of the measured data and improve the classification accuracy, transfer learning was introduced. Using the VGG-16 model, its accuracy was improved up to 97%. Additional experiments were conducted to ascertain the radar’s capability to detect the human voice through a barrier between the human and the radar. In this paper, we demonstrated the possibility of remote voice recognition using Doppler information, with or without a barrier.