Signal-to-clutter-and-noise Ratio Research Articles

Multiple Stationary Human Targets Detection in Through-Wall UWB Radar Based on Convolutional Neural Network

Ultra-wideband (UWB) impulse radar is widely used for through-wall human detection due to its high-range resolution and high penetration capability. UWB impulse radar can detect human targets in non-line-of-sight (NLOS) conditions, mainly based on the chest motion caused by human respiration. The automatic detection and extraction of multiple stationary human targets is still a challenge. Missed alarms often exist if the detection method is based on the energy of the human target. This is mainly because factors such as the range of the target, the intensity of the respiratory movement, and the shadow effect will make a difference between the energy scattered by targets. Weak targets are easily masked by strong targets and thus cannot be detected. Therefore, in this paper, a multiple stationary human targets detection method based on convolutional neural network (CNN) in through-wall UWB impulse radar is proposed. After performing the signal-to-clutter-and-noise ratio (SCNR) enhancement method on the raw radar data, the range-slow-time matrix is fed into a six-layer CNN. Benefiting from the powerful feature extraction capability of CNN, the target point of interest (TPOI) can be extracted from the data matrix. The clustering algorithm is used to simplify the TPOIs to achieve accurate detection of multiple targets behind the wall. The effectiveness of the proposed method is verified by the experimental data.

Through-the-wall high-dimensional imaging of human vital signs by combining multiple enhancement algorithms using portable LFMCW-MIMO radar

Radar-based life imaging technology has been widely applied in both civilian and military applications. Wall penetration attenuation degrades the signal-to-clutter-and-noise ratio (SCNR) and radar portability restricts the spatial resolution of the high-dimensional image. In this study, we constructed a portable linear-frequency continuous-wave(LFMCW) multiple-inputmultiple-output(MIMO) radar system, and we presented a novel high-dimensional imaging framework. We combined the maximum spectrum peak, fourth-order cumulant (FOC) and 3D coherent factor (CF) to enhance vital signs based on attention mechanism. We improve resolution by deconvolution algorithm using the data from a human dummy. Visualization-enhanced 4D point clouds images were created by mapping micro-doppler-frequency to color. We employed a series of experiments to validate the proposed method, including human and beagle imaging in free space, and short-range and long-range (16 m) human imaging through a wall. These high-dimensional imaging results validated the portable radar system’s potential in detection, identification, interpretation of human targets.

Slow-Time Code Design for Space-Time Adaptive Processing in Airborne Radar.

Space-time adaptive processing (STAP) techniques have been motivated as a key enabling technology for advanced airborne radar applications. In this paper, a slow-time code design is considered for the STAP technique in airborne radar, and the principle for improving signal-to-clutter and noise ratio (SCNR) based on slow-time coding is given. We present two algorithms for the optimization of transmitted codes under the energy constraint on a predefined area of spatial-frequency and Doppler-frequency plane. The proposed algorithms are constructed based on convex optimization (CVX) and alternating direction (AD), respectively. Several criteria regarding parameter selection are also given for the optimization process. Numerical examples show the feasibility and effectiveness of the proposed methods.

A novel hypersonic vehicle-borne multichannel SAR-GMTI scheme based on adaptive sum and difference beams within eigenspace

This paper investigates a novel ground moving target indication (GMTI) scheme for a hypersonic vehicle-borne multichannel synthetic aperture radar (MC-SAR) system with Doppler ambiguity. First, after the range compression and azimuth chirp Fourier transform (CFT), by applying the eigenspace-based adaptive sum and difference beams (EASDB) on the coarse-focused images, the high-precision cross-track velocity (CTV) can be retrieved. Then, utilizing the high-precision CTV to construct an accurate moving target steering vector to extract the moving target energy. With the proposed CFT-two-step method, we have avoided cumbersome CTV search, and simplified the process of range walk correction, resulting in lower computational complexity. Compared to the CFT-center and CFT-two-step methods, the proposed scheme obtains the accurate two-dimension motion parameters of a moving target, and has better performance and robustness in the detection, focusing, and location, preserving the moving target envelope and achieving higher signal-to-clutter-and-noise ratio (SCNR). Finally, using the processing results of simulation and real measured MC-SAR data, we verify the effectiveness and feasibility of our proposed scheme.

Moving Target Detection and Parameter Estimation via a Modified Imaging STAP with a Large Baseline in Multistatic GEO SAR

With the development trends of multistatic spaceborne synthetic aperture radar (SAR), geosynchronous SAR (GEO SAR) employing several formation-flying small satellites also has great potential for remote sensing. The small satellites can cooperate to acquire multi-channel data for moving target detection and parameter estimation in strong clutters. However, multistatic GEO SAR has large satellite spacing and a curved trajectory, which induce the near-field effects and channels out of alignment, respectively, bringing about challenges for the spatial adaptive processing. These problems produce a high-order term in the multi-channel slant range model, making the traditional model and adaptive processing method invalid. In this paper, to meet the requirement of SAR focusing, we firstly derive a fourth-order slant range model and a third-order path difference model for multistatic GEO SAR. Secondly, based on the derived model, the principle of stationary phase and series reversion method are utilized to derive the spatial steering vector for a moving target, which is a basis of spatial adaptive processing in the range-Doppler domain. Thirdly, the time-domain match filtering is constructed based on the fourth-order slant range model to image the moving target. Additionally, the moving targets are detected in the image domain. The motion parameter is estimated by iteratively maximizing the output signal to clutter and noise ratio (SCNR) through the range of possible target velocities. Finally, considering that the GEO SAR is still in development, the computer simulations are carried out to verify the effectiveness and evaluate the performance.

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.

Geosynchronous Spaceborne-Airborne Bistatic Moving Target Indication System: Performance Analysis and Configuration Design

Geosynchronous spaceborne-airborne bistatic synthetic aperture radar (GEO SA-BSAR), consisting of GEO transmitter and airborne receiver, has stable coverage for a long time and benefits moving target detection. However, the performance of GEO SA-BSAR moving target indication (MTI) system varies widely between bistatic configurations. The traditional configuration design for GEO SA-BSAR system only considers the imaging performance, which may cause the poor MTI performance. In this paper, we propose a bistatic configuration design method to jointly optimize the MTI and SAR imaging performance for GEO SA-BSAR MTI system. The relationship between the MTI performance and bistatic configuration parameters is derived analytically and analyzed based on the maximum output signal to clutter and noise ratio (SCNR) criterion. Then, the MTI performance and SAR imaging performance are jointly considered to model the configuration design problem as a multi-objective optimization problem under the constrained condition. Finally, the optimal configuration for GEO SA-BSAR MTI system is given.

Optimizing Transmit Sequence and Instrumental Variables Receiver for Dual-Function Complexity System

This correspondence deals with the joint cognitive design of transmit coded sequences and instrumental variables (IV) receive filter to enhance the performance of a dual-function radar-communication (DFRC) system in the presence of clutter disturbance. The IV receiver can reject clutter more efficiently than the match filter. The signal-to-clutter-and-noise ratio (SCNR) of the IV filter output is viewed as the performance index of the complexity system. We focus on phase only sequences, sharing both a continuous and a discrete phase code and develop optimization algorithms to achieve reasonable pairs of transmit coded sequences and IV receiver that fine approximate the behavior of the optimum SCNR. All iterations involve the solution of NP-hard quadratic fractional problems. The relaxation plus randomization technique is used to find an approximate solution. The complexity, corresponding to the operation of the proposed algorithms, depends on the number of acceptable iterations along with on and the complexity involved in all iterations. Simulation results are offered to evaluate the performance generated by the proposed scheme.

A Range Grating Lobes Suppression Method for Stepped-Frequency SAR Imagery

Stepped-frequency synthetic aperture radar (SAR) system errors induce the periodic magnitude error and phase error (MEPE) in the synthesized wideband spectrum. The periodic MEPE results in periodic grating lobes in the high range resolution profile, which degrade the SAR image quality seriously. This paper presents a data-driven grating lobes suppression (GLS) method, named MEPE-GLS, to suppress grating lobes by estimating and compensating the periodic MEPE. Based on the dominant targets' image domain data, MEPE-GLS estimates the phase error and magnitude error by the weighted maximum-likelihood estimation and weighted least-squares estimation, respectively. In order to improve the signal-to-clutter-and-noise ratio (SCNR) of the data employed in the MEPE estimation, MEPE-GLS applies the discrete windows to selected targets to remove clutters between two adjacent grating lobes. Compared with conventional GLS methods, MEPE-GLS removes grating lobes effectively while at the same time preserves the original image information, and has no restriction on hardware, scenes, and spectrum reconstruction methods. Simulation and real data experiments validate the effectiveness and robustness of MEPE-GLS.

An approach for refocusing of ground fast-moving target and high-order motion parameter estimation using Radon-high-order time-chirp rate transform

Long synthetic aperture time can improve the imaging quality of a ground moving target, whereas a moving target may be severely smeared in the cross-range image due to the range migration and the Doppler frequency migration. In this paper, the effects of the third-order Doppler broadening and Doppler ambiguity of a fast-moving target are considered. To address these issues, a novel motion parameter estimation method named high-order time-chirp rate transform (HTRT) is proposed, and then a new synthetic aperture radar (SAR) imaging method based on Radon-HTRT (RHTRT) for a ground moving target is developed. The major contributions are as follows: 1) The proposed SAR imaging method can eliminate the Doppler ambiguity effect. 2) The proposed method can realize longer time coherent integration than Radon–Fourier transform (RFT) and Radon–fractional Fourier transform (RFRFT) methods. 3) The proposed method is computationally efficient since HTRT can obtain the motion parameters of a moving target via performing the 2-dimensional (2-D) fast Fourier transform (FFT). Both the simulated and real data processing results show that the proposed method can finely image a ground moving target in a high signal-to-clutter and noise ratio (SCNR) environment.

Cognitive Space-Time Transmit Pattern Design

This paper provides a cognitive space-time (angle-Doppler) transmit pattern design method for mitigating clutter effect. This pattern takes full advantage of degrees-of-freedom (DOF) on transmit, which can preserve the maximum response for the target of interest while prenulling the mainlobe clutter on transmit, potentially simplifying processing on receiver and reducing the requirement for receiver dynamic range. The output signal-to-clutter-and-noise ratio (SCNR) can be improved significantly after applying the cognitive space-time transmit pattern to airborne-phased array radar. In addition, the traditional transmit antenna pattern and the proposed cognitive scheme are compared in terms of the probability of target detection. Simulations are conducted to demonstrate proof-of-concept.

Performance Analysis of Ground Moving Target Detection for Airborne MIMO Radar

The performance of a Ground Moving Target Indication (GMTI) radar is determined by the interference level of the clutter to a large extent. With the longer illumination and the larger aperture, Multiple-Input, Multiple-Output (MIMO) radar greatly enhances the ability to detect the slow-moving target. This paper compares MIMO radar with conventional phased-array radar in terms of signal to clutter and noise ratio (SCNR) performance. Moreover, the paper proves the fact that the improvement of SCNR with MIMO techniques is not only limited in the antenna configuration of the side-looking but also non-sidelooking array-antenna. The analysis of mianlobe clutter and sidelobe clutter levels can greatly simplify the computation of the total clutter. Finally, the experimental simulation is been given.

Stochastic Model Based Radar Waveform Design for Weapon Detection

We consider signature exploitation based waveform design for detection of weapons with a single-antenna monostatic radar. In order to account for the target signature variation with orientation and aspect angle, we model the target impulse response as a random process. For a weapon target, we show that the stochastic model based waveform significantly outperforms the commonly used chirp waveform in terms of the signal-to-clutter-and-noise ratio (SCNR) at the output of the receive filter, leading to an enhanced detection performance.

Phase-Modulated Waveform Design for Extended Target Detection in the Presence of Clutter

The problem to be addressed in this paper is a phase-modulated waveform design for the detection of extended targets contaminated by signal-dependent noise (clutter) and additive noise in practical radar systems. An optimal waveform design method that leads to the energy spectral density (ESD) of signal under the maximum signal-to-clutter-and-noise ratio (SCNR) criterion is introduced first. In order to make full use of the transmission power, a novel phase-iterative algorithm is then proposed for designing the phase-modulated waveform with a constant envelope, whose ESD matches the optimal one. This method is proven to be able to achieve a small SCNR loss by minimizing the mean-square spectral distance between the optimal waveform and the designed waveform. The results of extensive simulations demonstrate that our approach provides less than 1 dB SCNR loss when the signal duration is greater than 1 μs, and outperforms the stationary phase method and other phase-modulated waveform design methods.

Matched-Illumination Waveform Design for a Multistatic Through-the-Wall Radar System

We present the matched illumination waveform design for improved target detection in through-the-wall radar imaging and sensing applications. We consider a multistatic radar system for detection of stationary targets with known impulse responses behind walls. The stationary and slowly moving nature of typical indoor targets relaxes the orthogonality requirement on the waveforms, thereby allowing sequential transmissions from each transmitter with simultaneous reception at multiple receivers. The generalization of the matched illumination waveform design concept from a monostatic to a multistatic setting casts the indoor radar sensing problem in terms of multiple-input multiple-output (MIMO) operations and puts in context the offering of MIMO to urban sensing and imaging of targets in enclosed structures. Numerical electromagnetic modeling is used to provide the impulse response of typical behind-the-wall stationary targets, namely tables and humans, for different target orientations and at various incident and reflection angles. Simulation results depict an improvement in the signal-to-clutter-and-noise-ratio (SCNR) at the output of the matched filter receiver for multistatic radar as compared to monostatic operation.