range-Doppler Algorithm Research Articles

Ultra-wideband FMCW ISAR imaging with a large rotation angle based on block-sparse recovery

Ultra-wideband frequency modulated continuous wave (FMCW) radar has the ability to achieve high-range resolution. Combined with the inverse synthetic aperture technique, high azimuth resolution can be realized under a large rotation angle. However, the range-azimuth coupling problem seriously restricts the inverse synthetic aperture radar (ISAR) imaging performance. Based on the turntable model, traditional match-filter-based, range Doppler algorithms (RDAs) and the back projection algorithm (BPA) are investigated. To eliminate the sidelobe effects of traditional algorithms, compressed sensing (CS) is preferred. Considering the block structure of a signal at high resolution, a block-sparsity adaptive matching pursuit algorithm (BSAMP) is proposed. By matching pursuit and backtracking, a signal with unknown sparsity can be recovered accurately by updating the support set iteratively. Finally, several experiments are conducted. In comparison with other algorithms, the results from processing the simulation data, some simple targets, and a complex target indicate the effectiveness and superiority of the proposed algorithm.

An improved method for deceptive jamming against synthetic aperture radar

Jamming of synthetic aperture radar (SAR) is more difficult than the conventional radars because of its high processing gain. The defocusing of fake or virtual scatterers is the main problem that any jamming technique needs to tackle. An algorithm based on fractional Fourier transform is proposed for the efficient jamming of SAR. The results show that the performance of proposed algorithm is better than conventional Range Doppler Algorithm.

Improving SAR data processing with polarimetric reference functions in the range Doppler algorithm

ABSTRACTSynthetic aperture radar (SAR) is a form of radar that can be used to create images of objects and landscapes. The main important application of the polarimetric SAR can be found in surface and target decomposition process of its image processing. In this article, we propose a method of polarimetric SAR data processing using two new polarimetric reference functions of canonical targets with the intention to apply in coherent decompositions. Our experiment uses polarimetric backscatter characteristics of the dihedral and trihedral reflectors as the targets under a ground-based SAR geometry to create the polarimetric reference functions for azimuth compression in the SAR data processing. We process the data using Pauli decomposition to investigate the effect of our functions on the RGB (red, green, and blue) properties of the processed images. The results show that Pauli decomposition using our functions produces images with different distribution and intensity of RGB colours in the image pixels with some signs of improvement over the traditional range Doppler algorithm. This demonstrates that our polarimetric reference function can be used in the decomposition steps of the traditional SAR data processing and can potentially be used to reveal some useful quantitative physical information of target points of interest and improve image and surface classification.

GMTI and Parameter Estimation via Time-Doppler Chirp-Varying Approach for Single-Channel Airborne SAR System

Conventionally, a single-channel synthetic aperture radar (SC-SAR) system can hardly detect weak moving targets simply. In this paper, a time-Doppler chirp-varying (TDCV) filter is proposed for ground moving target indication and parameter estimation with the airborne SC-SAR system. The proposed method is easy to implement and mainly includes three steps. First, a traditional 2-D frequency range-Doppler algorithm is used to generate an original image. Second, the second-order range cell migration (RCM) phase term is partly compensated in the range frequency and azimuth time domain, and the rest of second-order RCM phase term is compensated in 2-D frequency domain. The whole processing, which is referred to as the TDCV approach, is employed to acquire a new TDCV image. Third, compared the original image with the new image, the clutter scatterers are nearly motionless while the moving targets are translated along the range direction due to their nonzero radial velocities. After the cancellation between two normalized images, the clutter background would be significantly suppressed since the two images generated by the same data. As a result, the moving targets can be indicated and the range difference of the moving target between two images can be exploited to estimate their radial velocities. The results obtained by applying the proposed method into a set of real SAR data are consistent with the analysis presented in this paper.

An Indirect Range-Doppler Algorithm for Multireceiver Synthetic Aperture Sonar Based on Lagrange Inversion Theorem

This paper presents a novel imaging algorithm which has the capacity of processing multireceiver synthetic aperture sonar (SAS) data based on Vu’s spectrum. There are two important issues when developing the fast Fourier-based imaging algorithms. One is the point target reference spectrum (PTRS) with analytical expression in the 2-D frequency domain; the other is the space variance of the PTRS. Vu has solved the first issue based on the Lagrange inversion theorem. However, the second issue has not been solved yet. Our approach in this paper is to apply Vu’s spectral result in an indirect range-Doppler (R-D) imaging algorithm. For each transmitter/receiver pair, the close-form azimuth modulation is derived first, and then, range/azimuth coupling can be obtained via the difference between the PTRS and the azimuth modulation. Unlike traditional R-D algorithm, which utilizes the interpolation operation to eliminate the range cell migration (RCM), the RCM correction (RCMC) in this paper is carried out through two steps, i.e., bulk RCMC and differential RCMC. Bulk RCMC accounts for the RCMC in one reference range. Differential RCMC accomplished with a range-dependent subblock postprocessing method is used to compensate for the space variant deviation phase error. Via the proposed method, the echoed signal corresponding to each transmitter/receiver pair is processed first. Following which, a high-resolution SAS complex image is obtained by coherent superposition of all the coarse subimages. Numerical simulations and real data processing results show that the proposed method has the similar focusing capabilities with the accurate back projection algorithm across the whole swath. Although the presented method has the disadvantage of latency, it is very easy to make a complete phase center approximation correction, allowing for the tandem nature of the collected data. Besides, the proposed algorithm can handle general case with explicit point of stationary phase (PSP) no matter how complicated the PSP is, and it is also suitable for the imagery of tandem synthetic aperture radar.

A Three-Dimensional Localization Method for Multistatic SAR Based on Numerical Range-Doppler Algorithm and Entropy Minimization

In traditional localization methods for synthetic aperture radar (SAR), the range sum estimation and Doppler centroid estimation (DCE) are required. The DCE error can influence the localization accuracy greatly. In addition, the target height information cannot be obtained by these methods. In this paper, a three-dimensional localization method for multistatic SAR based on the numerical range-Doppler (RD) algorithm and entropy minimization principle is proposed. In this method, the raw data from each transmitter and receiver (T/R) pair are focused by the numerical RD algorithm with the initial location value of the reference target. Then, Newton iteration is used to solve the target location value with the information of the bistatic range sum (BRS) in different SAR images with respect to different T/R pairs. Generally, the initial location value of the reference target is not accurate, and it can influence the imaging quality and accuracy of other target locations. We use entropy to measure image quality and iterate imaging with the new location value of the reference target, until the entropy gets the minimum value. Therefore, we can get the optimal location value of the reference target, which can make image entropy reach the minimum. Finally, all targets can be located by the Newton iteration method with their BRS in each T/R pair that are obtained from the images with minimum entropy. Compared with traditional localization methods for monostatic SAR, the proposed method not only effectively eliminates the influences of DCE errors, but also can get the target height information. Therefore, it improves the localization accuracy and can achieve three-dimensional localization. The effectiveness of the localization approach is validated by a numerical simulation experiment.

ISAR Imaging of Maneuvering Target Based on the Quadratic Frequency Modulated Signal Model With Time-Varying Amplitude

Inverse synthetic aperture radar (ISAR) imaging of maneuvering target plays an important role in the field of national defense and surveillance. In this case, the conventional range Doppler algorithm is unsuitable to generate a well-focused ISAR image due to the time-varying property of the Doppler frequency during the integrated imaging interval. Furthermore, the dihedral or trihedral components of the imaging target or the phenomena of migration through resolution cell for the target's complex motion will induce the time-varying performance of the amplitude for the received signal. In this paper, the received signal in a range bin is depicted as multicomponent quadratic frequency-modulated signal with time-varying amplitude, and the generalized cubic phase function is used to estimate the parameters of it. Associated with the range instantaneous Doppler technique, the images quality can be enhanced distinctly compared with the conventional constant amplitude signal model. Results of simulated and read data demonstrate the effectiveness of the novel algorithm proposed in this paper.

A study of the partial acquisition technique to reduce the amount of SAR data

Synthetic Aperture Radar (SAR) technology is capable to provide high resolution image data of earth surfaces from a moving vehicle. This causes large volumes of raw data. Many researchs were proposed about compressed radar imaging, which can reduce the sampling rate of the analog digital converter (ADC) on the receiver and eliminate the need of match filter on the radar receiver. Besides the advantages, there is a major problem that produces a large measurement matrix, which causes a very intensive matrix calculation. In this paper is studied a new approach to partial acquisition technique to reduce the amount of raw data using compressed sampling in both the azimuth and range and to reduce the computational load. The results showed that the reconstruction of SAR image using partial acquisition model has good resolution comparable to the conventional method (Range Doppler Algorithm). On a target of a ship, that represents a low level sparsity, a good reconstruction image could be achieved from a fewer number measurement. The method can speed up the computation time by a factor of 2.64 to 4.49 times faster than with a full acquisition matrix.

An analysis of Chosen Image Formation Algorithms for Synthetic Aperture Radar with FMCW

Abstract The modelling of FMCW SAR systems, due to long signal duration time, commonly used start-stop approximation for pulsed radars causes errors in the image. Continuous motion of the radar platform results in additional range-azimuth couplings and range walk term that should be considered in processing of signal from this type of radar. The paper presents an analysis of the following algorithms: Time Domain Correlation (TDC), Range Doppler Algorithm (RDA), and Range Migration Algorithm (RMA). The comparison of the algorithms is based on theoretical estimation of their computation complexity and the quality of images obtained on the basis of real signals of FMCW SAR systems.

A High Precision Terahertz Wave Image Reconstruction Algorithm.

With the development of terahertz (THz) technology, the applications of this spectrum have become increasingly wide-ranging, in areas such as non-destructive testing, security applications and medical scanning, in which one of the most important methods is imaging. Unlike remote sensing applications, THz imaging features sources of array elements that are almost always supposed to be spherical wave radiators, including single antennae. As such, well-developed methodologies such as Range-Doppler Algorithm (RDA) are not directly applicable in such near-range situations. The Back Projection Algorithm (BPA) can provide products of high precision at the the cost of a high computational burden, while the Range Migration Algorithm (RMA) sacrifices the quality of images for efficiency. The Phase-shift Migration Algorithm (PMA) is a good alternative, the features of which combine both of the classical algorithms mentioned above. In this research, it is used for mechanical scanning, and is extended to array imaging for the first time. In addition, the performances of PMA are studied in detail in contrast to BPA and RMA. It is demonstrated in our simulations and experiments described herein that the algorithm can reconstruct images with high precision.

Imaging of high‐speed manoeuvering target via improved version of product high‐order ambiguity function

This study presents a novel algorithm for radar imaging of high-speed manoeuvering target. It is based on the fact that the azimuth part of the echo is modelled as the superposition of multiple quadratic frequency modulated (QFM) signals, and the range-Doppler algorithm is inappropriate to generate a focused radar image in this case. In this study, the improved version of product high-order ambiguity function (IPHAF) is proposed to estimate the parameters of multiple QFM signals. This estimator requires only one-dimensional (1D) maximisations without the scaling operation compared with the traditional product high-order ambiguity function. The radar image quality can be improved by the IPHAF technique, and the experimental results validate the effectiveness of the method presented in this study.

A fast multichannel SAR raw data simulator of clutter and moving targets

Accessibility of a fast and accurate multichannel synthetic aperture radar raw data generator of stationary clutter and moving targets has high importance, especially in the application of ground moving target indication. In this paper, a fast four-stage algorithm for generating the raw data of each channel stationary clutter and moving targets, has been proposed respectively in the frequency and the hybrid time–frequency domain. Using this simulator, in different conditions in terms of target motion speed, acceleration and direction, for each of the channels, after generating the raw data, its final image has been extracted by the range-Doppler algorithm. Then, using clutter suppression techniques such as DPCA, ATI and hybrid DPCA–ATI, the multichannel SAR final image has been obtained in ideal and nonideal conditions. Finally, the obtained images of the first channel have been studied using the extracted formulas for predicting the effects of target motion parameters on the SAR images as well as analyzing the multichannel SAR final image. The results show that the proposed algorithm for generating the raw data of each channel stationary clutter and moving targets has better performance in terms of speed and accuracy than the other existing simulators and the proposed multichannel SAR simulation method has high quality.

ISAR Imaging of Targets With Complex Motions Based on a Noise-Resistant Parameter Estimation Algorithm Without Nonuniform Axis

In inverse synthetic aperture radar (ISAR) imaging of targets with complex motions, such as highly maneuvering airplanes and ships fluctuating with oceanic waves, azimuth echoes of a range cell have to be modeled as multicomponent cubic phase signals (CPSs) after the range alignment and the phase adjustment. Due to the time-varying Doppler frequencies of scatterers, ISAR image obtained with the standard range-Doppler algorithm is blurred, and the range-instantaneous-Doppler (RID) technique is required to improve the image quality. In this paper, by employing a novel parametric autocorrelation function and the generalized scaled Fourier transform, an effective parameter estimation algorithm is proposed for multicomponent CPSs and applied to reconstruct the RID image for targets with complex motions. Analyses of the implementation, the cross-term, the anti-noise performance, and the computational cost demonstrate that, compared with other three representative estimation algorithms, the proposed algorithm can eliminate the brute-force searching procedure and acquire a higher anti-noise performance without the nonuniform axis. Through simulations and analyses for synthetic models and the real radar data, we verify the effectiveness of the proposed estimation algorithm and the corresponding ISAR imaging algorithm.

A novel range-Doppler imaging algorithm with OFDM radar

Traditional pulse Doppler radar estimates the Doppler frequency by taking advantage of Doppler modulation over different pulses and usually it requires a few pulses to estimate the Doppler frequency. In this paper, a novel range-Doppler imaging algorithm based on single pulse with orthogonal frequency division multiplexing (OFDM) radar is proposed, where the OFDM pulse is composed of phase coded symbols. The Doppler frequency is estimated using one single pulse by utilizing Doppler modulation over different symbols, which remarkably increases the data update rate. Besides, it is shown that the range and Doppler estimations are completely independent and the well-known range-Doppler coupling effect does not exist. The effects of target movement on the performances of the proposed algorithm are also discussed and the results show that the algorithm is not sensitive to velocity. Performances of the proposed algorithm as well as comparisons with other range-Doppler algorithms are demonstrated via simulation experiments.

Synthetic aperture radar imaging using nonlinear frequency modulation signal

In this paper, a new nonlinear frequency modulation (NLFM) waveform is developed that can be used as a transmitted chirp in synthetic aperture radar (SAR) imaging to improve the imaging quality compared to a linear frequency modulation (LFM) chirp signal. The new NLFM is constructed based on piecewise linear functions, which are optimized using multi-objective optimization. Different signal processing algorithms are investigated in order to use NLFM as the transmitted chirp in a SAR system. In addition, a modified motion compensation (MC) algorithm using navigation data is proposed for the range-Doppler algorithm. Strip-map SAR geometry is considered to generate a SAR raw signal, in order to validate the new offered chirp signal and the proposed MC algorithm.

合成孔径声呐成像算法之CS算法仿真研究

距离多普勒算法是最为广泛的成像算法，但是存在两点不足：第一，当使用较长的核函数提高距离徙动精度时，运算量较大；第二，距离压缩对方位频率的依赖性难解决。Chirp Scaling算法(CSA)运用Papoulis提出的Scaling原理，通过相位相乘代替时域插值来完成随距离变化的RCMC，同时解决了距离压缩中对方位频率的依赖问题。 Range Doppler algorithm is the most extensive imaging algorithm, but it has two shortcoming: Firstly, When you use a longer kernel function to improve the accuracy of distance migration, it will cause a lot of computation burden; secondly, the compression of distance is dependency for the frequency of azimuth. The CSA uses the principle of scaling proposed by Papoulis. It uses phase multiply to finish the RCMC which is changed by distance, instead of the time-domain interpolation. It also solves the dependence between the compression of distance and the frequency of azimuth.

Extended Range Doppler Algorithm for Multiple-Receiver Synthetic Aperture Sonar Based on Exact Analytical Two-Dimensional Spectrum

For the imaging of multiple-receiver synthetic aperture sonar (SAS) under the nonstop-hop-stop case, an exact analytical solution for the two-dimensional (2-D) frequency spectrum is usually difficult to obtain because of the existence of the double-square-root (DSR) term in the range history equation. Several approximate solutions for the 2-D spectrum have been derived to focus the multiple-receiver SAS data. In this paper, the range history geometry for multiple-receiver SAS is newly constructed to meet the demand of the derivation of an analytical 2-D spectrum. According to the geometry-based bistatic formula (GBF) method, a quasi-analytical 2-D spectrum with an unknown variable named half quasi-bistatic angle (HQBA) is reviewed. Based on the method of series reversion (MSR), the fourth order equation with respect to the HQBA is solved and an analytical HQBA is obtained. After substituting the analytical HQBA into the quasi-analytical 2-D spectrum, a completely analytical 2-D spectrum is obtained and the problem of the 2-D spectrum derivation caused by the DSR term is solved successfully. In this paper, an extended range Doppler (RD) algorithm based on the derived 2-D spectrum is proposed for focusing the multiple-receiver SAS data under the non stop-hop-stop case. The results of simulation and real experiment data imaging have validated the effectiveness and accuracy of the proposed algorithm.

ISAR Imaging of Nonuniformly Rotating Targets Based on Generalized Decoupling Technique

For nonuniformly rotating targets, such as targets with complex motions and nonsevere maneuvering targets, the range migration and the time-varying Doppler frequency deteriorate inverse synthetic aperture radar (ISAR) image reconstructed with the conventional range-Doppler (RD) algorithm. In this paper, we focus on the scatterer-dependent Doppler spread compensation and present an efficient ISAR imaging algorithm for nonuniformly rotating targets by employing the symmetric parametric instantaneous autocorrelation function (SPIAF) and the generalized decoupling technique (GDT). It belongs to the range-instantaneous-Doppler (RID) technique and can be easily implemented by using the complex multiplication, the fast Fourier transform (FFT) and the nonuniform FFT (NUFFT). The implementation, the cross-term, the computational cost, and the antinoise performance are analyzed for the GDT-based ISAR imaging algorithm. With the synthetic data and the real radar data, comparisons with other three representative ISAR imaging algorithms demonstrate that the GDT-based ISAR imaging algorithm can acquire a higher antinoise performance and a better cross-term suppression with a moderate computational cost. In addition, with discussions of the characteristics, the generalities and the implementation methods for the SPIAF and the GDT, we indicate that these two new techniques may be applied in more realistic applications.

Focusing one‐stationary bistatic forward‐looking synthetic aperture radar with squint minimisation method

This study deals with the imaging problem of one-stationary bistatic forward-looking synthetic aperture radar (BFSAR). This BFSAR has extensive potential applications, such as self-navigation and self-landing in the airport. However, the forward-looking (or squint) angle is usually large in one-stationary BFSAR. It causes large range migration and strong range dependence on the secondary range compression term. Therefore it is difficult to use traditional imaging algorithms to focus one-stationary BFSAR. To solve this problem, an imaging algorithm based on squint minimisation method is proposed in this study. The squint minimisation operation can shear the high forward-looking angle data spectrum and decrease the coupling between range and azimuth. Then, the authors derive a modified range Doppler algorithm (RDA) to focus the sheared data. Numerical simulations show that by combining squint minimisation method and modified RDA, the raw data of one-stationary BFSAR can be well imaged.

Analysis of the Effect of Interference on InSAR

Various jamming techniques have been developed to prevent interferometric synthetic aperture radar from effective detection and observation. In this paper, a thorough analysis of the jamming effects on correlation and interferometric phase is provided. To derive the jamming result, a general signal model for the interference is first presented and the corresponding imaging results are produced through the range-Doppler algorithm. Then, the impacts of the interference on correlation are analyzed. The non-center located jammer decreases the correlation seriously due to the low correlation of the interference. However, the center located jammer clearly increases the correlation when the input jamming-to-signal ratio is large enough. Finally, the jammed interferometric phases for different jammer positions are discussed. It shows that the non-center located jammer results in large phase errors, while for the center located jammer, the interferometric phase approaches a constant. The effects of interference are demonstrated by simulated data based on the TerraSAR system.