Chirp Scaling Research Articles

Blind NCS-Based Autofocus for Airborne Wide-Beam SAR Imaging

The improvement in azimuth resolution and/or the increase in the instantaneous beam width can result in a wide-beam autofocus problem in airborne synthetic aperture radar (SAR). Because of the assumption of central-beam approximation, the typical two-step motion compensation (MoCo) method and its extensions are unsuitable for the autofocus of wide-beam SAR imaging. In addition, existing MoCo algorithms for airborne wide-beam SAR imaging require high-precision inertial navigation data. To address these problems, we propose a wide-beam autofocus algorithm based on a blind nonlinear chirp scaling. First, based on the two-step MoCo method, the wide-beam autofocus in this study was modeled as a multiparameter optimization problem for an optimal overall imagery quality. Subsequently, we combine the well-known parametric and nonparametric methods in the SAR autofocus community to convert the multidimensional optimization problem into a two-dimensional optimization problem. Furthermore, we observe that this two-dimensional optimization problem can be further converted into two one-dimensional optimization problems, which can significantly increase the efficiency and robustness of autofocus processing. In addition, the proposed method is a full-aperture algorithm for wide-beam SAR autofocus, which can avoid the problems of image stitching and phase discontinuity compared with well-known subaperture autofocus algorithms (e.g., SATA, PTA, and FD). The processing results of the simulated and measured data verified the effectiveness of the proposed method.

Nonlinear Chirp Scaling Imaging Method for Three-Dimensional Foresight Linear Array Maneuvering SAR

Linear array maneuvering synthetic aperture radar (SAR) can push the limitations of classical SAR on foresight 3-D imaging, which has captured the attentions of worldwide radar researchers for a long time. To reconstruct the position of foresight target, this paper puts forward a nonlinear chirp scaling method for 3-D foresight linear array maneuvering SAR (FLAM-SAR). According to the novel geometry configuration, a nonlinear chirp scaling operation is adopted to equalize the space-variant Doppler frequency modulation rate. The simulation results of the array point scatterers and real airplane target model are used to prove the validity of theoretical derivation and validate the 3-D imaging capacity of FLAM-SAR.

A Sparse Imaging Method for Frequency Agile SAR

Frequency agility increases the difficulty of jammers to predict and estimate the carrier frequency and, thus, improves the radar electronic counter-countermeasures (ECCM) performance. In this article, frequency agility is introduced into synthetic aperture radar (SAR). The characteristic of the Doppler history of frequency-agile SAR (FASAR) is analyzed, which shows that the azimuth compression could not be achieved by the classic imaging algorithms. In order to reconstruct the images of interested targets, a three-channel sparse imaging method is proposed based on approximated observation model by using the echo data of different carrier frequencies. By deriving the equivalent observation model, it is concluded that the reconstruction performance can be enhanced by improving the coherence of match filter imaging results in different channels. The image characteristic of different channels in FASAR is analyzed based on the chirp scaling imaging operator. A phase compensation method is then proposed to improve the coherence of images of interested targets in different channels. Specifically, the SAR mode of random frequency agility is proposed to improve the reconstruction performance. Finally, simulations are carried out to demonstrate the effectiveness of imaging methods and ECCM performance. Theoretical analysis and simulation results demonstrate that images generated in random FASAR have better performance than those in stepped FASAR. By performing the phase compensation, the reconstruction performance of small targets can be significantly improved.

Frequency-Scaling-Based Spaceborne Squint SAR Sparse Imaging

In synthetic aperture radar (SAR), due to the characteristics of squint data in spaceborne imaging geometry, a more accurate range cell migration correction (RCMC) operation is necessary. Furthermore, imaging degradation due to ignoring range-variant filtering needed for secondary range compression (SRC) limits SAR imaging. In addition, due to enormous computational complexity required for squint SAR data processing, the existing imaging methods, for instance, chirp scaling algorithm (CSA) and range-Doppler algorithm (RDA) are no longer sufficient, especially for large-scale scenes. In order to solve above problems, this paper presents a novel spaceborne squint SAR sparse imaging method, which could not only eliminate the effects of squint to a certain extent, but also improve the performance of focused SAR image. Compared with matched filtering (MF) based squint imaging algorithm, the proposed method can obtain the SAR images with higher quality from full- or down-sampled echo data.

A Real-Time Unified Focusing Algorithm (RT-UFA) for Multi-Mode SAR via Azimuth Sub-Aperture Complex-Valued Image Combining and Scaling

Spaceborne synthetic aperture radar (SAR) can operate at various modes, including stripmap mode, spotlight mode, sliding spotlight mode, and Terrain observation by progressive scans (TOPS) mode. These four imaging modes can be regarded as unified, differing in rotation-center ranges. To uniformly focus the data of these four imaging modes in real-time, this article proposes a real-time unified focusing algorithm (RT-UFA) for the multi-mode SAR via azimuth sub-aperture complex-valued image combining and scaling. The imaging processing can be performed while the data are being recorded. In the first stage of imaging, sub-aperture complex-valued images with relative low-resolution can be obtained by the cascade of the extended chirp scaling (ECS) and azimuth dechirp. Then, these complex-valued images are coherently combined by shifting the integer number of pixels, and thus the full-resolution image of all the recorded data can be obtained. The azimuth scaling and the pixels shifting in the RT-UFA are analyzed in detail. Simulation and SAR data results are presented to validate the analysis and RT-UFA.

A Novel Weighted Amplitude Modulation (WAM) System for Ambiguity Suppression of Spaceborne Hybrid Quad-Pol SAR

Quadrature-polarimetric synthetic aperture radar (quad-pol SAR) has extensive applications, including climate zones classification, extraction of surface roughness, soil moisture mapping, moving target indication, and rice mapping. Hybrid quad-pol SAR ameliorates the range ambiguity performance of conventional quad-pol SAR. However, the azimuth ambiguity of its cross-polarized (cross-pol) echo signals is serious, limiting the swath width of SAR. Therefore, this paper proposes a spaceborne weighted amplitude modulation (WAM) full-polarimetric (full-pol) SAR system, and it can suppress the azimuth ambiguity of hybrid quad-pol SAR. The performance boost of the azimuth ambiguity by the two imaging modes of the proposed SAR system is detailed and evaluated with the L-band system parameters. Moreover, the chirp scaling algorithm (CSA) is adopted to execute scene simulations for the two imaging modes. The results indicate that the proposed SAR system can effectively suppress the azimuth ambiguity of hybrid quad-pol SAR and verify the theoretical analysis.

Wide‐bandwidth signal‐based multireceiver SAS imagery using extended chirp scaling algorithm

Traditional chirp scaling algorithm is often developed based on the quadratic approximation of point target reference spectrum, which neglects the higher-order coupling between range and azimuth dimensions. Besides, the scaling operation is conducted based on quadratic term of reference range, and the residual quadratic error increases with target range far away from reference range. The analysis of phase error shows that both errors are noticeable under the case of wide-bandwidth signal, and the imaging performance would be seriously distorted. To solve this problem, the higher-order coupling and quadratic error are compensated by exploiting sub-block processing method in the range dimension when the chirp scaling algorithm is exploited to reconstruct targets. Compared to traditional methods, the presented method significantly improves the focussing performance based on the simulation results. The processing of real data further shows that the performance of presented method is superior to that of traditional method.

Modified Chirp Scaling Algorithm for Ultra-High Resolution Spaceborne-SAR

The hyperbolic range equation model (HREM) and equivalent squint range model (ESRM) are applied in traditional chirp scaling algorithm (CSA). However, these range models cannot describe the satellite range history in the high-resolution case accurately because of the long azimuth integration time. The non-negligible phase error caused by this will lead the targets distort. In this paper, a modified chirp scaling algorithm (MCSA) is proposed by introducing a novel high-precision range model. A more accurate signal spectrum is calculated through it. Then, the modified chirp scaling factor, range compression filter, range cell migration correction (RCMC) filter and azimuth compression filter can be derived based on this signal spectrum, and the focused target obtained at last. Finally, the experimental results, to validate the proposed algorithm, adopted by the sliding spotlight synthetic aperture radar (SAR) simulation are provided.

A two-step channel mismatch estimation and compensation method for distributed MC SAR

ABSTRACT A distributed multichannel synthetic aperture radar system refers to a multichannel synthetic aperture radar system with channels distributed and installed at different locations on the platform. It is a promising system for high-resolution wide-swath imaging. The channels of the distributed multichannel synthetic aperture radar are sparsely distributed and have long cross-track baselines. The range-variant envelope migration and phase mismatch in the echoes between different channels are introduced by the long cross-track baselines and affect the performance of azimuth signal reconstruction. The sparsity of channels results in the poor correlation of data between channels, so the time-domain cross-correlation method typically used in azimuth multichannel synthetic aperture radar cannot be used in distributed multichannel synthetic aperture radar to estimate channel phase error directly. In this paper, the gain-phase error, sampling time delay and slant range difference introduced by cross-track baselines are modelled uniformly as channel mismatches. Firstly, a two-step channel mismatch estimation and compensation method for distributed multichannel synthetic aperture radar is proposed. Secondly, a range-variant envelope migration compensation method based on the chirp scaling principle is given. Thirdly, this paper also presents the processing of data rearrangement based on the distribution of spatial sampling points to make the time-domain cross-correlation method suitable for distributed multichannel synthetic aperture radar. Point target simulation and scene simulation are provided to show the effectiveness of the proposed methods.

Single-chip multi-processing architecture for spaceborne SAR imaging and intelligent processing

The satellite-borne SAR image intelligent processing system needs to process on-orbit real-time imaging and various tasks of applications, for which reason designing a dedicated high-efficient single-chip multi-processor is of prioritized necessity that can simultaneously satisfy requirements of real-time and low power consumption. Aiming at on-chip data organization and memory access structure, two typical models of SAR(synthetic aperture radar) imaging CSA (chirp scaling) and neural network VGG-11 are analyzed, and then a collaborative computing model for the intelligent processing on remote sensing is extracted. A strip Tile data processing scheme and a dedicated multi-processing architecture is not only proposed, but a data organization and a caching strategy of Tile space synchronization splicing is also presented. In addition, the designed data caching structure among the processing units greatly reduces off-chip access memory bandwidth while supporting parallel pipeline execution of multi-task model. The chip adopts 28 nm CMOS technology featuring with merely 1.83 W of the overall power consumption, whose throughput and energy efficiency reaches 9.89TOPS and 5.4 TOPS/W, respectively. The present architecture can improve real-time performance of the on-orbit remote sensing intelligent processing platform while reducing the complexity of system designing, which is highly adaptive to differentiated expansions according to different models of algorithm.

Focusing highly squinted missile-borne SAR data using azimuth frequency nonlinear chirp scaling algorithm

Focusing highly squinted missile-borne SAR data using azimuth frequency nonlinear chirp scaling algorithm

Focus Improvement of Airborne High-Squint Bistatic SAR Data Using Modified Azimuth NLCS Algorithm Based on Lagrange Inversion Theorem

In this paper, a modified azimuth nonlinear chirp scaling (NLCS) algorithm is derived for high-squint bistatic synthetic aperture radar (BiSAR) imaging to solve its inherent difficult issues, including the large range cell migration (RCM), azimuth-dependent Doppler parameters, and the sensibility of the higher order terms. First, using the Lagrange inversion theorem, an accurate spectrum suitable for processing airborne high-squint BiSAR data is introduced. Different from the spectrum that is based on the method of series reversion (MSR), it is allowed to derive the bistatic stationary phase point while retaining the double square root (DSR) of the slant range history. Based the spectrum, a linear RCM correction is used to remove the most of the linear RCM components and mitigate the range-azimuth coupling, and, then, bulk secondary range compression is implemented to compensate the residual RCM and cross-coupling terms. Following this, a modified azimuth NLCS operation is applied to eliminate the azimuth-dependence of Doppler parameters and equalize the azimuth frequency modulation for azimuth compression. The experimental results, with better focusing performance, prove the high accuracy and effectiveness of the proposed algorithm.

A Simple Algorithm for Compensation for Range Cell Migration in a Stripmap SAR

Introduction. Range Cell Migration (RCM) is a source of image blurring in synthetic aperture radars (SAR). There are two groups of signal processing algorithms used to compensate for migration effects. The first group includes algorithms that recalculate the SAR signal from the "along–track range – slant range" coordinate system into the "along-track range – cross-track range" coordinates using the method of interpolation. The disadvantage of these algorithms is their considerable computational cost. Algorithms of the second group do not rely on interpolation thus being more attractive in terms of practical application.Aim. To synthesize a simple algorithm for compensating for RCM without using interpolation.Materials and methods. The synthesis was performed using a simplified version of the Chirp Scaling algorithm.Results. A simple algorithm, which presents a modification of the Keystone Transform algorithm, was synthesized. The synthesized algorithm based on Fast Fourier Transforms and the Hadamard matrix products does not require interpolation.Conclusion. A verification of the algorithm quality via mathematical simulation confirmed its high efficiency. Implementation of the algorithm permits the number of computational operations to be reduced. The final radar image produced using the proposed algorithm is built in the true Cartesian coordinates. The algorithm can be applied for SAR imaging of moving targets. The conducted analysis showed that the algorithm yields the image of a moving target provided that the coherent processing interval is sufficiently large. The image lies along a line, which angle of inclination is proportional to the projection of the target relative velocity on the line-of-sight. Estimation of the image parameters permits the target movement parameters to be determined.

Processing of Bistatic SAR Data With Nonlinear Trajectory Using a Controlled-SVD Algorithm

The nonlinear trajectory and bistatic characteristics of general bistatic synthetic aperture radar (SAR) can cause severe two-dimensional space-variance in the echo signal, and therefore it is difficult to focus the echo signal directly using the traditional frequency-domain imaging algorithm based on the assumption of azimuth translational invariance. At present, the state-of-the-art nonlinear trajectory imaging algorithm is based on singular value decomposition (SVD), which has the problem that SVD may be not controlled, and thus may lead to a high imaging complexity or low imaging accuracy. Therefore, this article proposes a nonlinear trajectory SAR imaging algorithm based on controlled SVD (CSVD). First, the chirp scaling algorithm is used to correct the range space-variance, and then SVD is used to decompose the remaining azimuth space-variant phase, and the first two feature components after SVD are integrated to make them be represented by a new feature component. Finally, the new feature component is used for interpolation to correct the azimuth space-variance. The simulation results show that the proposed CSVD can further improve the image quality compared with SVD-Stolt.

Focusing Nonparallel-Track Bistatic SAR Data Using Modified Frequency Extended Nonlinear Chirp Scaling

Unsynchronization of the separate transmit–receive beams makes it a challenging task to obtain high-quality images for nonparallel-track bistatic synthetic aperture radar (NP-BiSAR). To accommodate this issue, we propose an imaging configuration where the receiver’s beam follows the transmitter’s one actively by adjusting the squint angle of receiver. And a frequency extended nonlinear chirp scaling (FENLCS) algorithm is modified to cope with new effects introduced by the innovative configuration, which is based on an improved quadratic ellipse model. Based on the new model, some innovative improvements on image formation are made, including a residual azimuth-dependent high-order range cell migration correction (ADH-RCMC) and a rederived FENLCS that takes highly varying Doppler centroid into consideration, which contribute to better imaging quality. Simulation results validate the effectiveness of the proposed configuration and algorithm.

An Efficient Algorithm Based on CSA for THz Stepped-Frequency SAR Imaging

An efficient algorithm based on chirp scaling algorithm (CSA) for terahertz (THz) stepped-frequency (SF) synthetic aperture radar (SAR) imaging is proposed in this letter. We call this efficient algorithm SF-CSA for convenience. THz imaging techniques have good prospects in the fields of military, public safety, and nondestructive defect identification. In these fields, real-time imaging is very important. CSA is an efficient algorithm suitable for SAR real-time imaging, but it can be only used for linear frequency-modulation (LFM) SAR imaging. The main contribution of this letter is the successful application of CSA in THz SF SAR imaging. Compared with other existing THz SF SAR imaging algorithms, SF-CSA has higher efficiency and is more suitable for real-time imaging. The validity of SF-CSA is demonstrated by theoretical derivation, simulation, and experiment in this letter. In the simulation and experiment, the radar operates at 300 GHz providing a maximum bandwidth of 28.8 GHz, leading to a range resolution of 5.2 mm. The simulation and experiment results show that SF-CSA has high quality and efficiency for THz SF SAR imaging.

A novel AFNCS algorithm for super-resolution SAR in curve trajectory

With the improvement of SAR resolution, super-resolution SAR imaging is more and more widely used in the all-time and all-weather video surveillance and remote sensing imaging. One implementation of super-resolution SAR is that radar works in the spotlight mode. In the case with highly squinted angle and acceleration, the azimuth space variance and the coupling between range and azimuth will become serious in super-resolution imaging. Thus, an azimuth frequency nonlinear chirp scaling algorithm is proposed to solve this problem. Based on the acceleration model, the accurate 2-D spectrum is performed by adopting the method of series reversion. The space-variance of missile-borne SAR in curved flight path is analyzed and an azimuth polynomial phase filter is constructed to make the coefficients of the perturbation function has sufficient flexibility to eliminate the spatial-variant couple terms between range and azimuth. In addition, the gradient operation is used to expand the space-variant coefficients of azimuth modulation term, and the perturbation function is applied to eliminate the space-variant in azimuth direction. The proposed focusing method can process the missile-borne SAR data obtained in spotlight mode in highly squinted angle with high efficiency. The simulation results verify the effectiveness of the proposed imaging approach. The integration of the research in this paper and the deep learning will further pave the way of super-resolution SAR imaging applications in disaster monitoring, security and surveillance.

Squinted Airborne Synthetic Aperture Radar Imaging with Unknown Curved Trajectory.

The imagery of airborne highly squinted synthetic aperture radar (SAR) with curved trajectory is a challenging task due to the translational-variant range cell migration (RCM) and azimuth modulation. However, in most cases of practical application, the curved trajectory cannot be accurately known, which brings greater difficulties to the imaging problem. To accommodate these issues, we propose a novel motion modelling and optimisation based imaging algorithm for the highly squinted SAR with unknown curved trajectory. First, to correct the translational-variant RCM, a coarse-to-fine RCM correction scheme as well as a range perturbation approach is applied. Afterwards, an optimisation model of motion information under the criterion of minimum entropy is built during the azimuth processing by nonlinear chirp scaling (NLCS). Correspondingly, a differential evolution (DE) optimisation strategy is proposed to estimate the motion information in an iterative manner. We empirically compare the proposed algorithms with several state-of-the-art highly squinted curved SAR imaging algorithms. Numerical results show the effectiveness of the proposed method in the case without any prior information of the curved trajectory.

Time-Varying Baseline Error Estimation and Compensation in UAV SAR Interferometry Based on Time-Domain Subaperture of Raw Radar Data

The rigid oscillation and flexible deformation baseline errors occur in dual-antenna unmanned aerial vehicle (UAV) SAR interferometry (InSAR). The errors caused by airflow disturbances and UAV platform mechanical oscillation will lead to interferometric phase undulation. Measuring the errors has high requirements for length and time accuracy for the equipment. In this paper, a time-varying baseline error (TBE) estimation and compensation method based on continuous time-domain subaperture data is proposed. Firstly, we model the TBE and derive its expression in each subaperture image focused by the chirp scaling dechirp (CS-dechirp) algorithm. Then it is possible to extract the estimated differential TBE (D-TBE) from the differential interferogram of overlapping scenes in subaperture images. Further, the full-aperture TBE can be obtained through an integration of the estimated D-TBE. Finally, the full-aperture compensation can be accomplished by a phase correction after the range variation estimation. Taking advantage of the time-domain subaperture, the D-TBE phases are sampled at each subaperture center time, and the proposed method can be well combined with a motion compensation algorithm in the processing flow for UAV InSAR. Furthermore, the case of low coherence is overcome. The results of simulation and real measured airborne single-pass dual-antenna data validate the proposed approach.

Bistatic Forward-Looking SAR MP-DPCA Method for Space–Time Extension Clutter Suppression

Echoes of bistatic forward-looking synthetic aperture radar (BFSAR) disperse to multiple range cells and exist spatial frequency extension as well as Doppler spectrum extension (i.e., namely space–time extension). Furthermore, the characteristics of BFSAR clutter are strongly nonstationary and spatial variants. Because of the abovementioned issues, clutter and moving targets are fully overlapped in the initial 3-D space–time–range raw data domain, and the clutter cannot be suppressed effectively. To solve this problem, a BFSAR multipulse displaced phase center antenna (MP-DPCA) method is proposed in this article. First, keystone transform without Doppler ambiguity is applied to remove the coupling between the space–time and range domains. Hence, the overall complex 3-D processing in the space–time–range domain is reduced to independent 2-D processing in each space–time domain. Subsequently, a spatial-dechirp processing is applied in the space–time domain to eliminate the spatial frequency extension. Meanwhile, Doppler parameters of clutter point scatterers are equalized by nonlinear chirp scaling processing in the frequency and time domains. Accordingly, the Doppler spectrum extension of point scatterers can be eliminated by a uniform azimuth dechirp processing. After aforesaid three steps, the clutter and moving targets are separated in the space–time domain. Finally, based on the linear phase difference of clutter between the channels, a multipulse canceller can be designed to suppress the clutter. Compared with the existing space–time adaptive procession (STAP) and DPCA methods, this method not only overcomes the nonstationary problem in BFSAR but also conquers the strict application conditions of DPCA. Simulation results are given to verify the effectiveness of the proposed method.