INSTANTANEOUS DOPPLER FREQUENCY FOR SQUINT SAR IMAGING

Instantaneous Doppler frequency for squint SAR imaging has been found with ChirpScaling Algorithm (CSA). Because the azimuth sample is not perpendicular to the range sample,the range signal must impact on the azimuth signal in the squint SAR data processing, andthe different slant range targets have different Doppler frequencies. From the mathematicalmodel of SAR echo signal, this paper carefully analyzes the instantaneous azimuth frequency, theinstantaneous Doppler frequency component of the azimuth frequency and the impact of rangechirp on azimuth frequency, which explains that Doppler frequency should be properly selected forcorrect SAR imaging in the squint SAR. The results of point target simulation experiments showthat the way is reasonable for the squint SAR and can effectively complete range compressionand azimuth focusing, and improve images' quality.

SAR Image Coregistration Using Fringe Definition Detection

In order to overcome the limitation of cross correlation coregistration method for Synthetic Aperture Radar （SAR） interferometric pairs with low coherence, a new image coregistration algorithm based on Fringe Definition Detection （FDD） is presented in this paper. The Fourier transformation was utilized to obtain spectrum characteristics of interferometric fringes. The ratio between spectrum mean and peak was proposed as the evaluation index for identifying homologous pixels from interferometric images. The satellites ERS-1/2 C-band SAR acquisitions covering the Yangtze River plain delta, eastern China and ALOS/PALSAR L-band images over the Longmen Shan mountainous area, southwestern China were respectively employed in the experiment to validate the proposed coregistration method. The testing results suggested that the derived Digital Elevation Model （DEM） from FDD method had good agreement with that from the cross correlation method as well as the reference DEM at high coherence area. However, The FDD method achieved a totally improved topographic mapping accuracy by 24 percent in comparison to the cross correlation method. The FDD method also showed better robustness and achieved relatively higher performance for SAR image eoregistration in mountainous areas with low coherence.

IMPROVED ALGORITHM FOR STRIPMAP SAR IMAGING

This paper proposes a calibrated method for quasi-broadside side-looking mode SAR imaging with small squint angle and an improved method named as phase alignment algorithm of subaperture reference signal. The calibrated method adopts subaperture spotlighting algorithm of broadside mode to image the real data of quasi-broadside mode SAR, then based on the obtained image the small squint angle is estimated and the calibrated subaperture spotlighting algorithm of squint mode is employed to obtain the final image. The calibrated method can calibrate the abnormal region and obtain the correct image. The phase alignment algorithm of subaperture reference signal adjusts phases of respective subaperture reference signals in order to make them be in phase and constructs a new spotlighting window function for SAR imaging. Theoretical analysis shows that with the same sample data, the improved method can increase SAR imaging area in azimuth dimension. The methods are verified by the results of computer simulation.

OPTIMIZATION ON ANTENNA PATTERN OF SPACEBORNE SAR WITH IMPROVED NSGA-Ⅱ

Optimization of antenna array pattern used in a spaceborne Synthetic Aperture Radar (SAR) system is considered in this study. A robust evolutionary algorithm, Non-dominated Sorting Genetic Algorithms (the improved NSGA-Ⅱ), is applied on a spaceborne SAR antenna pattern design. The system consists of two objective functions with two constraints. Pareto fronts are generated as a result of multi-objective optimization. After being validated by a test problem ZDT4, the algorithms are used to synthesize spaceborne SAR antenna radiation pattern. The good results with low Ambi- guity-to-Signal Ratio (ASR) and high directivity are obtained in the paper.

UNSUPERVISED POLINSAR CLASSIFICATION BASED ON OPTIMAL COHERENCE SET

Aiming to solve the misclassification problems of unsupervised polarimetric Wishart clas- sification algorithm based on Freeman decomposition, an unsupervised Polarimetric Synthetic Aper- ture Radar （SAR） Interferotnery （PolInSAR） classification algorithm based on optimal coherence set parameters is studied and proposed. This algorithm uses the result of Freeman decomposition to divide the image into three basic categories including surface scattering, volume scattering, and double-bounce Then, the PolInSAR optimal coherence set parameters are used to finely divide each of the three basic categories into 9 categories, and the whole image is divided into 27 categories. Because both the Freeman decomposition result and optimal coherence set parameters indicate specific scattering characteristics, the whole image is merged into 16 categories based on physical meaning. At last, the Wishart cluster is employed to obtain the final classification result. To preserve the purity of scattering characteristics, pixels with similar scattering characteristics are restricted to be classified with other pixels. The final classification results effectively resolve the misclassification problem, not only the buildings can be effectively distinguished from vegetation in urban areas, but also the road is well distinguished from grass. In this paper, the E-SAR PolInSAR data of German Aerospace Center （DLR） are used to verify the effectiveness of the algorithm.

Monitoring cyanobacteria-dominant algal blooms in eutrophicated Taihu Lake in China with synthetic aperture radar images

Monitoring algal blooms by optical remote sensing is limited by cloud cover.In this study,synthetic aperture radar(SAR) was deployed with the aim of monitoring cyanobacteria-dominant algal blooms in Taihu Lake in cloudy weather.The study shows that dark regions in the SAR images caused by cyanobacterial blooms damped the microwave backscatter of the lake surface and were consistent with the regions of algal blooms in quasi-synchronous optical images,confirming the applicability of SAR for detection of surface blooms.Low backscatter may also be associated with other factors such as low wind speeds,resulting in interference when monitoring algal blooms using SAR data alone.After feature extraction and selection,the dark regions were classified by the support vector machine method with an overall accuracy of 67.74%.SAR can provide a reference point for monitoring cyanobacterial blooms in the lake,particularly when weather is not suitable for optical remote sensing.Multi-polarization and multi-band SAR can be considered for use in the future to obtain more accurate information regarding algal blooms from SAR data.

光释光测年中石英颗粒全球标准曲线法(gSGC)与单片再生法(SAR)等效剂量(D_e)的比对

全球标准曲线法(gSGC)的提出为高效快速地测定释光样品的等效剂量(De)值提供了可能。但是由于各个实验室的放射源剂量率、操作流程、仪器误差以及选取的再归一化剂量值等不同,每个实验室得出的gSGC会有参数的不同。通过建立实验室的gSGC曲线和测试流程,并比较gSGC法和SAR法获取的De值的一致性,发现在低剂量范围内(0~100 Gy),使用gSGC法估计的De和SAR法估计的De非常接近,表明在低剂量范围内用gSGC法估计De是可靠的。这将很大程度地提高本实验室的释光测年速度,同时也为其他实验室gSGC的建立提供借鉴。在较高剂量范围(>100 Gy)与SAR方法结果比对时出现较大差别,这可能是由于研究中用于拟合gSGC的样品数量不够多,尤其是年龄较老的样品还不够多,还需在今后工作中逐步积累更多样品,完善gSGC参数,使其也能胜任较老年龄样品。

ADAPTIVE KURTOSIS OPTIMIZATION AUTOFOCUS ALGORITHM

This paper proposes an autofocus algorithm used for Synthetic Aperture Radar (SAR) images, called Adaptive Kurtosis Optimization Autofocus Algorithm (AKOAA). The AKOAA can reduce the differ-ence between initial value and real value in focusing by adaptively adjusting the initial value, therefore effec-tively improve the local extremum problem in the Contrast Optimization Autofocus Algorithm (COAA) and speed up the convergence velocity. The principle and realization method of AKOAA are thoroughly investi-gated, and experimental results using real L-band SAR data show that the focus speed of AKOAA is nearly doubled compared with that of the COAA, and the image contrast of AKOAA is improved as well.

Denoising of SAR Images Based on Lifting Scheme Wavelet Packet Transform

According to the different characteristics that signal and noise exhibit during wavelet decomposition, a new denoising method based on the lifting scheme wavelet packet decomposition is presented. In this method, the SAR images are decom- posed by using the best wavelet packet and the norm of each sub-band are calculated; signals and noise can be discriminated based on the norm and soft-threshold method, and the images can be denoised. Experiments show that the proposed algorithm has excellent performance in denoising SAR images, and can remove most noise of images with well-kept texture detail informa- tion. The calculating speed of the method is twice the speed of the general wavelet packet transform algorithm.

A feature extraction method for synthetic aperture radar(SAR) automatic target recognition based on maximum interclass distance

Synthetic aperture radar(SAR) automatic target recognition is an important application in SAR.How to extract features has restricted the application of SAR technology seriously.In this paper,a new feature extraction method for SAR automatic target recognition based on maximum interclass distance is proposed,which integrates class and neighborhood information.This method can reinforce discriminative power using maximum interclass distance,so it can improve recognition rate effectively.

Recent progress in Bistatic SAR with illuminators of opportunity

Bistatic SAR（Bi SAR）with illuminators of opportunity is a kind of flexible SAR system that consists of non-cooperative transmitters and a stationary or moving receiver,as Figure 1shows.In recent years,notable efforts have been made to promote the development of this kind of system.Progress regarding Bi SAR with navigation satellites as transmitters before 2015,including the related theory and practice,has been well reviewed by Antoniou et al.and can be referred from[1].This paper reviews some of the progress in 2015and 2016,including novel signal processing approaches,advanced Bi SAR system configurations and potentially

A nonparametric estimation of the infection curve

Predicting the future course of an epidemic depends on being able to estimate the current numbers of infected individuals.However,while back-projection techniques allow reliable estimation of the numbers of infected individuals in the more distant past,they are less reliable in the recent past.We propose two new nonparametric methods to estimate the unobserved numbers of infected individuals in the recent past in an epidemic.The proposed methods are noniterative,easily computed and asymptotically normal with simple variance formulas.Simulations show that the proposed methods are much more robust and accurate than the existing back projection method,especially for the recent past,which is our primary interest.We apply the proposed methods to the 2003 Severe Acute Respiratory Syndorme(SARS) epidemic in Hong Kong.

Focusing Azimuth-Invariant Bistatic Synthetic Aperture Radar Data Based on a Polynomial Model

In this paper,a focusing approach is presented to widen the use of efficient monostatic imaging algorithms for azimuth-invariant bistatic synthetic aperture radar(SAR) data.The bistatic range history is modeled by a polynomial of azimuth time.Using this model,an analytic form of the signal spectrum in the 2D frequency domain is derived,and a simple single-valued relation between the transmitter and receive ranges is established.In this way,a lot of monostatic image formation algorithms can be extended for the bistatic SAR data,and a bistatic chirp scaling algorithm is developed as an application of the new approach.This algorithm can be used to process the azimuth-invariant bistatic configuration where the transmitter and receiver platforms are moving on parallel tracks with the same velocity.In addition,some simulation results are given to demonstrate the validity of the proposed approach.