Target Range Information Research Articles

Target ranging via sparse non-uniform short-time fractional Fourier transformation for multi-parameter modulated signal

Multi-parameter modulated signal can improve the anti-interception ability yet makes the range extraction of the target inconvenient. To solve the problem, a novel scaling transformation combined with the non-uniform short-time fractional Fourier transformation is proposed to effectively acquire the target range information. Unlike the traditional methods, the influence of the varied carrier frequency is firstly mitigated by the proposed scaling transformation. Then, the error caused by the period-varying is relieved by the sampling conversion in the digital domain. Further, the corresponding dictionary is constructed to accomplish the ranging information searching and extracting. Simulation results show that the proposed method can mitigate the impact of multiple varied parameters on signal processing. The detection error could be reduced by 67.9% after using the proposed method.

Non-Line-of-Sight Multi-Target Localization Algorithm for Driver-Assistance Radar System

In automatic driving, it is difficult for automotive radar to capture the information of vehicles and pedestrians located in blind areas such as street corners and urban intersections, which may lead to collision risks. To deal with it, this paper investigates the problem of multiple target localization in a non-line-of-sight (NLOS) scenario. Specifically, first, the propagation paths of the electromagnetic waves in the L-shaped NLOS scenario are analyzed and a multipath echoes model for the multiple-input-multiple-output (MIMO) radar is established. Then, the time of arrivals (ToAs) with respect to different paths are estimated by the matrix pencil algorithm. Based on the estimated delays, a path recognition strategy, by fully considering the range and angle information of targets, is proposed to pair the ToAs with different types of multipath and targets. Finally, the performance of the proposed method is verified via simulations and experiments, which reveal that the positions of the NLOS targets can be estimated with high precision.

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.

Signal Source Localization with Long-Term Observations in Distributed Angle-Only Sensors.

Angle-only sensors cannot provide range information of targets and in order to determine accurate position of a signal source, one can connect distributed passive sensors with communication links and implement a fusion algorithm to estimate target position. To measure moving targets with sensors on moving platforms, most of existing algorithms resort to the filtering method. In this paper, we present two fusion algorithms to estimate both the position and velocity of moving target with distributed angle-only sensors in motion. The first algorithm is termed as the gross least square (LS) algorithm, which takes all observations from distributed sensors together to form an estimate of the position and velocity and thus needs a huge communication cost and a huge computation cost. The second algorithm is termed as the linear LS algorithm, which approximates locations of sensors, locations of targets, and angle-only measures for each sensor by linear models and thus does not need each local sensors to transmit raw data of angle-only observations, resulting in a lower communication cost between sensors and then a lower computation cost at the fusion center. Based on the second algorithm, a truncated LS algorithm, which estimates the target velocity through an average operation, is also presented. Numerical results indicate that the gross LS algorithm, without linear approximation operation, often benefits from more observations, whereas the linear LS algorithm and the truncated LS algorithm, both bear lower communication and computation costs, may endure performance loss if the observations are collected in a long period such that the linear approximation model becomes mismatch.

Improved MUSIC Method against Range Dimension Deceptive Jamming Based on FDA-MIMO

Frequency diverse array-multiple-input multiple-output (FDA-MIMO) radar makes it transmit beam range–angle two-dimensional freedom by attaching a small frequency offset increment between the array elements. With the widespread use of digital radio frequency memory (DRFM) technology, it is able to delay the false target to any range bin and doppler unit by delaying and forwarding the radar transmits signals, resulting in the deceptive jamming effect of range dimension. To this end, based on the research of the existing main-lobe deceptive interference methods, this paper proposes a new improved MUSIC method based on the FDA-MIMO radar against deceptive jamming in the range dimension. Firstly, the range information of target and jamming is determined through spatial spectrum search by using the mismatch of jamming in the airspace position and range bin position, and then the process of range dimension deceptive jamming suppression is given. The simulation analysis results show that the proposed anti-jamming method can effectively mitigate against range dimension deceptive jamming.

Adaptive Distributed Target Detection for FDA-MIMO Radar in Gaussian Clutter Without Training Data

Since frequency diverse array multiple-input multiple-output (FDA-MIMO) radar possesses additional target range information for potential performance improvement, this article studies adaptive distributed targets detection for FDA-MIMO radar, where the targets are embedded in Gaussian clutter with unknown covariance matrix. The proposed FDA-MIMO radar detection model considers also the distributed targets occupying several secondary range cells, which is different from the classic detection models in multiple-input multiple-output (MIMO) and/or phase array (PA) radars that discuss only point-like targets. By exploiting the FDA-MIMO radar framework for distributed target detection, we propose the detector through a two-step generalized likelihood ratio test criteria without the need of training data and/or a priori covariance matrix. Moreover, closed-form expressions for the probability of false alarm and detection probability are derived, respectively. The proposed detector adheres to the property of a constant false alarm rate because its probability of false alarm is not restricted by the covariance matrix. The proposed method together with all theoretical analysis are verified by numerical results.

Distributed Two-Dimensional MUSIC for Joint Range and Angle Estimation with Distributed FMCW MIMO Radars.

To estimate range and angle information of multiple targets, FMCW MIMO radars have been exploited with 2D MUSIC algorithms. To improve estimation accuracy, received signals from multiple FMCW MIMO radars are collected at the data fusion center and processed coherently, which increases data communication overhead and implementation complexity. To resolve them, we propose the distributed 2D MUSIC algorithm with coordinate transformation, in which 2D MUSIC algorithm is operated with respect to the reference radar’s coordinate at each radar in a distributed way. Rather than forwarding the raw data of received signal to the fusion center, each radar performs 2D MUSIC with its own received signal in the transformed coordinates. Accordingly, the distributed radars do not need to report all their measured signals to the data fusion center, but they forward their local cost function values of 2D MUSIC for the radar image region of interest. The data fusion center can then estimate the range and angle information of targets jointly from the aggregated cost function. By applying the proposed scheme to the experimentally measured data, its performance is verified in the real environment test.

Underwater 3D Doppler-Angle Target Tracking with Signal Time Delay.

The traditional target tracking is a process of estimating the state of a moving target using measurement information obtained by sensors. However, underwater passive acoustic target tracking will confront further challenges, among which the system incomplete observability and time delay caused by the signal propagation create a great impact on tracking performance. Passive acoustic sensors cannot accurately obtain the target range information. The introduction of Doppler frequency measurement can improve the system observability performance; signal time delay cannot be ignored in underwater environments. It varies with time, which has a continuous negative impact on the tracking accuracy. In this paper, the Gauss–Helmert model is introduced to solve this problem by expanding the unknown signal emission time as an unknown variable to the state. This model allows the existence of the previous state and current state at the same time, while handling the implicit equations. To improve the algorithm accuracy, this paper further takes advantage of the estimated state and covariance for the second stage iteration and propose the Gauss–Helmert iterated Unscented Kalman filter under a three-dimensional environment. The simulation shows that the proposed method in this paper shows superior estimation accuracy and more stable performance compared with other filtering algorithms in underwater environments.

Phase-coded modulation 3D ghost imaging

A three-dimensional ghost imaging system based on the phase-coded modulation is proposed. The system utilizes two high speed electro-optic modulators to encode and decode the pulsed laser with the M-sequence so as to accomplish correlation calculation in optical domain to solve the range information of targets. Compared with the conventional optical heterodyne ghost imaging system using complex detection devices to guarantee heterodyne efficiency, the phase-coded modulation three-dimensional ghost imaging is capable of easy implement and similar detection performance. The results of numerical simulation and experiment have verified the feasibility of the proposed phase-coded modulation three-dimensional ghost imaging.

Frequency diverse array with random logarithmically increasing frequency offset

AbstractThe frequency diverse arrays (FDAs) have been extensively investigated since it can provide a unique angle‐range‐dependent beampattern. This range‐dependent characteristic can suppress the range ambiguous clutters, leading to many novel potential Radar applications. Two issues, however, exist in conventional FDA (CFDA) beampatterns, that is, range‐angle coupling and range periodicity. Therefore, for a CFDA Radar, target range information cannot be obtained directly from the beampattern peaks and target ambiguity occurs in the range domain. In this work, a new frequency diverse array (FDA) transmitter architecture with random logarithmically increasing frequency offset (log‐RFDA) is presented. It is shown that the proposed strategy provides a nonperiodic thumbtack‐like beampattern, eliminating the ambiguity in range domain, suffered in the CFDA Radar. Furthermore, reduced side lobe and higher detection resolution can be achieved, compared with the previously reported log‐FDA.

Closed-Form Asymptotic Approximation of Target’s Range Information in Radar Detection Systems

The echoes of the radar systems can provide useful information about the target, including range, velocity, shape, and angular direction. Extensive studies have utilized the information of the target to improve system performance, whereas the problem of a favorable closed-form asymptotic approximation of the target's range information (RI) is seldom investigated. In this paper, we address the problem of obtaining a closed-form asymptotic approximation of the target's RI in all SNR regions for radar detection systems. The RI is formulated as the mutual information (MI) between the random range and the received signals with complex additive white Gaussian noise (CAWGN). The basis of our scheme is to employ the a posteriori probability density function (PDF) of the range to extract RI from the echoes. We show the a posteriori PDF is a function of the autocorrelation function (ACF) of signal and the cross-correlation function (CCF) of signal-noise. By dividing the integration interval of the a posteriori PDF into the signal-noise interval and noise interval, a closed-form asymptotic approximation of RI is derived based on the probability of range distinguishability and the normalized a posteriori entropies of low and high signal-to-noise ratio (SNR). The results also reveal an interesting relationship between the RI and the uncertainty of the target. As special cases, the closed-form approximations of RI in low and high SNR are obtained. Moreover, for the problem of slightly looser in medium SNR approximation, a better approximation is derived based on a linear model approach. Numerical results are presented to validate the proposed theory and verify the effectiveness of the proposed approximation.

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).

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.

Joint DOD and DOA Estimation in Bistatic MIMO Radar With Distributed Nested Arrays

In this paper, we investigate the problem of joint direction of departure (DOD) and the direction of arrival (DOA) estimation in bistatic MIMO radar. A new bistatic MIMO radar with the distributed nested array is proposed. Based on the new array, the DOD and DOA estimation algorithm called automatically paired DR-ESPRIT based on the angle disambiguation algorithm by using the range information of targets is proposed. By designing distributed nested array and using Khatri-Rao product processing, the long baseline and short baseline in the transceiver arrays are virtually extended simultaneously. The non-ambiguous and high-accuracy sine estimations of the DOD and DOA can be accomplished using DR-ESPRIT algorithm and the range information of targets and the geometry of bistatic MIMO radar. The virtual extension of array aperture and high angle estimation accuracy can be achieved for the MIMO radar with automatic pairing and without increasing the number of antennas compared with traditional uniform linear MIMO array. And, the proposed corresponding algorithm gives significant improvement in the DOD and DOA estimation performance. The simulation results validate the theoretical algorithm.

Vital Sign Signal Extraction Method Based on Permutation Entropy and EEMD Algorithm for Ultra-Wideband Radar

The noncontact measurement of vital sign signals is useful for medical care, rescuing disaster survivors from ruins and public safety. In this paper, a novel vital sign signal extraction method based on permutation entropy (PE) and ensemble empirical mode decomposition (EEMD) algorithm is proposed. The proposed algorithm analyzes the permutation entropy of radar-received pulses; the range between a human target and ultra-wideband (UWB) radar can be obtained by permutation entropy. Permutation entropy represents the complexity of signals, so we can use PE to select and recombine human life signals that are distributed in the adjacent distance gate. Moreover, EEMD algorithm is adopted to decompose the combined signal into intrinsic mode functions (IMF), and both the respiration and the heartbeat signals are reconstructed by IMF via reaching the energy threshold in the time domain. Experiments are carried out using UWB radar. Compared with traditional algorithms, the proposed algorithm can be used to extract the range and frequency information of human targets efficiently and accurately.

Airborne Near Infrared Three-Dimensional Ghost Imaging LiDAR via Sparsity Constraint

Three-dimensional ghost imaging LiDAR via sparsity constraint (3D GISC LiDAR), as a staring imaging method, can obtain both the range information and spatial distribution of a remote target with a single-pixel time-resolved detector. However, previous demonstrations mainly focused on the relatively static scene in visible light. Here we propose an airborne near infrared 3D GISC LiDAR system and airborne high-resolution imaging is implemented. Experimental results show that an image with 0.48 m horizontal resolution as well as 0.5 m range resolution at approximately 1.04 km height can be achieved. Some considerations on the improvement of this LiDAR system are also discussed.

Multihypothesis-Based Compressive Sensing Algorithm for Nonscanning Three-Dimensional Laser Imaging

The resolution of nonscanning three-dimensional (3-D) imaging systems is limited by the number and accuracy of the array sensors. Moreover, for space-continuous targets in practical situations, the echo pulses in time-of-flight systems overlap and traditional peak detection is no longer suitable for super-resolution applications. Hence, compressive sensing (CS) has been introduced to achieve super-resolution. However, most of the conventional CS algorithms cannot be used directly for 3-D image reconstruction. In this paper, we propose a novel super-resolution algorithm for nonscanning 3-D laser imaging based on CS reconstruction. To acquire the range information of space-continuous targets, an all-one projection is implemented in advance to estimate the spatial distribution of the targets; a range observation matrix composed of time-interval basis vectors is then constructed to obtain the peak values of each frame from overlapping echo pulses. Because of the spatial continuity of the targets, Tikhonov regularization is utilized to solve the ill-posed inverse problem. Furthermore, to enhance the reconstruction quality of the adjacent frames, multihypothesis prediction is used with displacement and diffusion models to estimate the motion of the contour line. Simulation results based on real data from the ASTER global digital elevation model demonstrate the effectiveness and high accuracy of the proposed algorithm for complex landforms.

A Portable FMCW Interferometry Radar With Programmable Low-IF Architecture for Localization, ISAR Imaging, and Vital Sign Tracking

This paper presents a portable radar system for short-range localization, inverse synthetic aperture radar imaging, and vital sign tracking. The proposed sensor incorporates frequency-modulated continuous-wave (FMCW) and interferometry (Doppler) modes, which enable this radar system to obtain both absolute range information and tiny vital signs (i.e., respiration and heartbeat) of human targets. These two different operation modes can be switched through an on-board microcontroller. To simplify the system, the proposed radar utilizes the audio card of a laptop to sample the baseband signal. The FMCW mode of the radar uses operational-amplifier-based circuits to generate an analog sawtooth signal and a reference pulse sequence (RPS). The RPS is locked to the sawtooth signal to obtain coherence for the radar system. For the interferometry mode, a low-intermediate-frequency modulation method is implemented to avoid the slow vital signs from being distorted by the high-pass filter of the audio card. Several experiments were carried out to reveal the capability and distinct operational features of the proposed portable hybrid radar. The experiments also showed that the system can easily detect glass, which is usually difficult to identify for optical-based sensors. In addition, 2-D scanning in a complex environment revealed that the proposed radar was able to differentiate human targets from other objects. Moreover, ISAR images were used to isolate moving human targets from surrounding clutter. Finally, the proposed radar also demonstrated its ability to accurately measure vital signs when a human subject sits still.

Improving the Imaging Quality of Ghost Imaging Lidar via Sparsity Constraint by Time-Resolved Technique

Ghost imaging via sparsity constraint (GISC)—which is developing into a new staring imaging lidar—can obtain both the range information and spatial distribution of a remote target with the use of the measurements below the Nyquist limit. In this work, schematics of both two-dimensional (2D) and three-dimensional (3D) GISC lidar are introduced. Compared with the 2D GISC lidar, we demonstrate by both simulation and experimentally that the signal-to-noise ratio of the 3D GISC lidar can be dramatically enhanced when a time-resolved technique is used to record the target’s reflection signals and the orthogonal characteristic of the target’s 3D surface structure is taken as a priori in the image reconstruction process. Some characteristics of the 2D and 3D GISC lidar systems are also discussed.

잠수함 선배열소나의 허위표적 정보를 이용한 표적의 거리추정 기법

In this paper, we propose target range estimation method using ghost target in the submarine linear array sonar. Usually, when submarine detect target, they use passive sonar detection to avoid self-disclosure by active sonar transmission. But, originally, passive linear array sonar have limitation for target range estimation and additional processing is required to get target range information. For the case of near-field target, typical range estimation method is using multiple information by multipath effect in underwater environment. Acoustic signal generated from target are propagated along with numerous multipath in underwater environment. Since multipath target signals received in the linear array sonar have different conic angles each other, ghost target is appeared at the bearing different with real target bearing and sonar operator can find these information on the operation console. Under several assumption, this geometric properties can be analysed mathematically and we get the target range by derivation of this geometric equations using measured conic angles of real target and ghost target.