Wide Nonlinear Chirp Scaling Algorithm for Spaceborne Stripmap Range Sweep SAR Imaging

The speed and direction of a missile shifts sharply in the dive phase, making the azimuth frequency modulation (FM) rate change with the azimuthal position, leading to azimuth ambiguities and image distortion. To solve this problem, a modified nonlinear chirp scaling (NLCS) algorithm was adopted to compensate for the azimuth FM rate. First, the geometric configuration and echo signal model of the spaceborne missile bistatic synthetic aperture radar (SAR) were built, and then the Doppler frequency correction was performed, and the 2-D spectrum of the signal was derived by the method of series reversion. Next, range migration correction and range compression were finished in the 2-D frequency domain. Following this, a modified NLCS algorithm was proposed to solve the space variance of Doppler phase problem. After compensating for the azimuth FM rate, the azimuth compression focusing was completed and the imaging result was obtained. Finally, by comparing the calculation amount, imaging effect, and performance index with the traditional NLCS algorithm, it can be concluded that the algorithm reduced the calculation amount by 1.0128 × 108 floating point operations per second (FLOPs) compared with the traditional NLCS algorithm, and the azimuth focusing effect of the edge point was greatly improved. Its resolution, peak sidelobe ratio (PSLR), and integrated sidelobe ratio (ISLR) were improved by 0.87 m, 3.32 dB, and 1.79 dB, respectively, which proved the effectiveness and feasibility of this method.

In this paper, some improvements of the Non-linear Chirp Scaling (NCS) algorithm for squint SAR imaging are discussed and a modified NCS is described. The improvements make the NCS applicable to process highly squinted SAR data with a large range swath and a high resolution. The reference frequency in the original algorithm, which is squint angle dependent, is also replaced by a constant factor in he modified NCS, and this makes the algorithm much feasible for implementation.

An extended nonlinear chirp scaling (NLCS) algorithm is proposed to process data of highly squinted, high-resolution, missile-borne synthetic aperture radar (SAR) diving with a constant acceleration. Due to the complex diving movement, the traditional signal model and focusing algorithm are no longer suited for missile-borne SAR signal processing. Therefore, an accurate range equation is presented, named as the equivalent hyperbolic range model (EHRM), which is more accurate and concise compared with the conventional fourth-order polynomial range equation. Based on the EHRM, a two-dimensional point target reference spectrum is derived, and an extended NLCS algorithm for missile-borne SAR image formation is developed. In the algorithm, a linear range walk correction is used to significantly remove the range-azimuth cross coupling, and an azimuth NLCS processing is adopted to solve the azimuth space variant focusing problem. Moreover, the operations of the proposed algorithm are carried out without any interpolation, thus having small computational loads. Finally, the simulation results and real-data processing results validate the proposed focusing algorithm.

Bistatic forward-looking SAR is a synthetic aperture radar system with an independently moving transmitter and receiver breaks through the limitations of the conventional monostatic SAR on the forward-looking imaging. However, the existence of a double hyperbola in the bistatic range equation makes the severe two–Dimension (2-D) coupling. Based on the bistatic SAR space geometrical model and the point target spectrum form the series reversion, this paper deals with above problems with the Second-Keystone and the nonlinear chirp scaling (NCS) algorithm. The results of simulation verify the feasibility of the method.

This paper mainly introduces a high-performance system of real-time Ultra Wide-Band (UWB) SAR processing. Firstly, the sub-aperture Nonlinear Chirp Scaling (NCS) algorithm is optimized and selected to form the UWB SAR image, and then it is mapped to the Multiple Digital Signal Processor (Multi-DSP) board. Secondly, the timing sequence of the realtime processing is analyzed, and the processing time of each task is measured. Finally, the simulation result of the realtime UWB SAR processing is given. (4 pages)

Squint multi-receiver synthetic aperture sonar (SAS) data is more challenging to process than data about its common side-looking counterpart because the geometry is complicated. While traditional multi-receiver algorithms mainly handle general side-looking cases, they do not work well for squint cases. Up to now, no multi-receiver algorithm for handling squint multi- receiver SAS data has been reported. This paper focuses on an imaging algorithm for the squint multi-receiver SAS. Firstly, the “non-stop-go-stop” signal model is established for squint multi- receiver SAS. Then a squint multi-receiver nonlinear chirp scaling algorithm (SMANLCSA) is proposed that is suited to process multi-receiver SAS data with small squint angle and SMANLCSA involves three key steps. The first step is to turn squint multi-receiver data into squint single-receiver data. The second step is a Doppler centroid frequency shift. The third step is range cell migration correction using nonlinear chirp scaling. Simulations have shown that SMANLCSA can handle squint multi-receiver data more accurately and effectively than the previous algorithm..

Bistatic Synthetic Aperture radar (BiSAr) is named for its unique separated transmitting and receiving platforms, which has the advantages of high security, flexible configuration, and strong information acquisition capabilities, and has broad application prospects. Aiming at the problem that the performance of traditional BiSAr imaging algorithms degrades sharply when facing complex squint and space-variant scenes, this paper proposes a Near-range Wide-Swath imaging algorithm for NP BiSAr based on a three-dimensional ellipsoid model. Firstly, a range pre-processing operation is used to eliminate the range cell migration (rCM) space-variant error introduced by the squint angle. Then, aiming at the high-order rCM residual amount after processing, a correction method based on a three-dimensional ellipsoid model is explored, and the improvement in accuracy of the three-dimensional ellipsoid model is verified by comparing the simulation with the second-order phase error of the traditional ellipsoid model. In response to the consistency requirement of Doppler parameters during azimuth compression, the three-dimensional ellipsoid model is combined into the Extended Frequency Nonlinear Chirp Scaling (EFNLCS) algorithm with residual Doppler centroid correction capability, which eliminates the residual Doppler centroid while improving the space-variant equalization capability of Doppler phase parameters. Finally, simulation experiments verify that the algorithm has better focusing processing capability and better applicability to near-range wide-swath scenes.

A nonlinear chirp scaling algorithm (NCSA) is proposed for bistatic SAR data processing with high squint angles in tandem configuration. Besides the dependence of the azimuth frequency, the dependence of range is considered for the Doppler chirp rate of tandem bistatic SAR. The proposed algorithm can compensate the range dependence of both the range cell migration (RCM) and the second range compression (SRC) terms well by appropriately setting the coefficients of the phase term, which is obtained after the nonlinear chirp scaling process in the two-dimensional wavenumber domain. Only fast Fourier transforms (FFTs) and phase multiplies are required, and fast imaging is implemented in the frequency domain. Satisfying focusing qualities verify the effectiveness of the proposed algorithm by simulations.

During the data acquisition of a squint terrain observation by progressive scan (TOPS) synthetic aperture radar (SAR), the steering of the antenna main beam increases the azimuth bandwidth and results in the azimuth signal aliasing in the Doppler domain. Besides, the range curvature and the Doppler frequency modulation (FM) rates after linear range walk correction are azimuth-variant for squint TOPS SAR. These problems may cause some difficulties for the SAR data processing. To deal with the problems, a new imaging algorithm for the squint TOPS SAR is introduced in this paper. After linear range walk correction, the azimuth preprocessing is implemented to achieve the two-dimensional frequency spectrum without aliasing. Then, utilizing a modified chirp scaling algorithm, we complete the range cell migration correction (RCMC) and range compression to the TOPS SAR data without subaperture. Finally, the frequency nonlinear chirp scaling (FNCS) is proposed to correct the variation of the FM rates and the azimuth signal is focused in the Doppler domain via the spectral analysis (SPECAN) method. Both simulation and real data results show the effectiveness of the proposed algorithm.

A CA-NCS algorithm in curve trajectory for smart global village

The forward-looking imaging problem of synthetic aperture radar (SAR) can be resolved by adopting the bistatic configuration. A bistatic configuration with a stationary transmitter and a forward-looking receiver is introduced and the two-dimensional spectrum is derived, and then an improved nonlinear chirp scaling algorithm is used to focus the data. The imaging quality is compared with the traditional nonlinear chirp scaling algorithm; the simulation results verify the 2D imaging ability of the proposed method.

In the processing of high-resolution wide-swath spaceborne synthetic aperture radar data, the slant range history is difficult to formulate with a high accuracy over a long data-acquisition interval, and the variation of the imaging parameters over the illuminated scene makes it necessary to implement 2-D space-variant processing. To deal with these issues, first, a slant range expression is derived based on a geometry model using a circular arc to approximate the curved trajectory in this paper, which is composed of a hyperbolic term, a cubic term, and a quartic term. Then, the imaging flow based on the slant range model is proposed: a cubic filtering in range is employed to normalize the range-variant secondary range compression; the nonuniform fast Fourier transform (NUFFT) is used to correct the additional range displacement introduced by the cubic filtering and the nonlinear range cell migration (RCM) caused by the range dependence of the velocity; necessary modifications are made on the matched filter for azimuth compression to accommodate the cubic filtering in range and to deal with the high-order terms of the slant range model. The simulation results show that the proposed slant range model has a relatively high accuracy; the range processing procedure that involves an NUFFT following a cubic filtering can apply to the case where the nonlinear chirp scaling algorithm is adopted, and it has the advantage of being capable of dealing with the nonlinear RCM; the azimuth processing procedure can provide satisfactory focusing qualities over a rather large azimuth extent.

This paper studies the performance of the frequency-domain algorithms (FDAs) for low-frequency ultra-wideband synthetic aperture radar (UWB SAR) data processing. First, a generalized theoretical derivation of the FDAs is presented from the viewpoint of SAR signal processing. The derivation not only provides a deeper understanding to the imaging principle of the extended Omega-K algorithm (EOKA), but also makes it compatible and comparable with the other FDAs. Second, the performance comparison on different FDAs is made based on theoretical analysis, simulation and experimental data. The comparison results show that the Omega-K algorithm (ωKA) has the highest imaging precision in the ideal case (i.e, no motion error), but its application is limited by the poor ability of compensating motion errors. In contrast, the EOKA and nonlinear chirp scaling algorithm (NCSA) have excellent performance on dealing with the motion error, but they can only be applied under specific preconditions. Besides, as cetner frequency gets lower, the fractional bandwidth and integration angle get larger, the imaging precision of NCSA greatly decreases, while the ωKA and EOKA still keep high precision.

The amount of echo data is huge in highly squinted synthetic aperture radar (SAR) imaging with high resolution. To solve this problem, the imaging method for highly squinted SAR with under-sampled echo data based on Compressed Sensing is put forward. Firstly, a Non-linear Chirp Scaling (NCS) imaging method with the Nyquist-sampled echo data is proposed. And then, the NCS operator is established based on the imaging method. Combining the NCS operator and Compressed Sensing theory, a novel highly squinted SAR imaging scheme is formulated. With the proposed method, just a small amount of imaging data is required for highly squinted SAR imaging. Finally, the effectiveness of the proposed method is proved by the imaging simulations.

Occurrence of periodical gapping in synthetic aperture radar (SAR) raw data poses a challenge in obtaining focused images. Traditional SAR imaging algorithms fail to process the periodically gapped raw data. A method is proposed to solve this problem. The presented method consists of phase compensation and recovering raw data in range Doppler domain via generalised orthogonal matching pursuit. Then, the recovered raw data is capable of being processed with the traditional SAR imaging algorithms. The Omega‐K algorithm is selected to focus the reconstructed raw data. The presented method is validated on performing better in comparison with the spectral method periodically gapped amplitude and phase estimation by point target simulation and analysis. In simulation, the raw data loses 50% by the form of azimuth periodical gapping. The resolution of point targets can reach 0.25 m in both azimuth and range direction. In addition, real SAR raw data is utilised to verify the effectiveness of the proposed method.