High Speed Maneuvering Platform Squint TOPS SAR Imaging Based on Local Polar Coordinate and Angular Division

This paper proposes an imaging algorithm for synthetic aperture radar (SAR) mounted on a high-speed maneuvering platform with squint terrain observation by progressive scan mode. To overcome the mismatch between range model and the signal after range walk correction, the range history is calculated in local polar format. The Doppler ambiguity is resolved by nonlinear derotation and zero-padding. The recovered signal is divided into several blocks in Doppler according to the angular division. Keystone transform is used to remove the space-variant range cell migration (RCM) components. Thus, the residual RCM terms can be compensated by a unified phase function. Frequency domain perturbation terms are introduced to correct the space-variant Doppler chirp rate term. The focusing parameters are calculated according to the scene center of each angular block and the signal of each block can be processed in parallel. The image of each block is focused in range-Doppler domain. After the geometric correction, the final focused image can be obtained by directly combined the images of all angular blocks. Simulated SAR data has verified the effectiveness of the proposed algorithm.

Review on Deinterlacing Algorithms

Interlacing is a commonly used technique for doubling the perceived frame rate without adding bandwidth in television broadcasting and video recording. During playback, however, it exhibits disturbing visual artifacts such as flickering and combing. As a result in modern display devices, video deinterlacing is used where the interlaced video format is converted to progressive scan format to overcome the limitations of interlaced video. This conversion is achieved through interpolating interlaced video. Current deinterlacing approaches either neglect temporal information for real-time performance but poor visual quality, or estimate motion for better deinterlacing but higher computational cost. This paper focuses on surveying the deinterlacing algorithms which apply both spatial and temporal-based methods and focus on different aspects of both motion-adaptive, non-motion adaptive, and the time complexity through these implementations.

Suppressing Paired Echoes Caused by Stair-Step Antenna Steering in TOPS SAR Imaging

The use of electronically steered antennas in the azimuth dimension typically leads to a staircase-like antenna beam steering law in the Terrain Observation by Progressive Scan (TOPS) wide-swath synthetic aperture radar (SAR) data acquisition mode, which will introduce paired echoes in the focused images. This paper proposes a new approach for removing such paired echoes from TOPS SAR images based on the generalization of the ideal optimum filtering concept, which can be implemented easily in the SAR data processing. Modeling the amplitude-modulated azimuth signal shows that the absolute phase of the introduced paired echoes cannot be determined due to the random rotation angle jump time for each target, which will prevent the precise use of optimum filtering. An extended optimum filtering approach, which is originally proposed for suppressing the azimuth ambiguities in SAR images, is reintroduced in this particular case, and a new approximated and generalized form of the deconvolving filtering in the approach is redefined to accommodate the undetermined phase for both the strongest paired distortion peaks and the other peripheral peaks in the distorted impulse response function (IRF). Simulated data from a TOPS SAR mode with staircase-like beam steering are used to verify the improvement in image quality by using the new method.

Deep Learning Algorithms Applied to the Classification of Video Meteor Detections

The application of a class of advanced machine learning techniques, namely deep learning, has been applied to automating the confirmation/classification of potential meteor tracks in video imagery. Deep learning is shown to perform remarkably well, even surpassing human performance, and will likely supplant the need for human visual inspection and review of collected meteor imagery. When applied to time series measurements of meteor track centroid positions and integrated intensities obtained from each video frame, a recurrent neural network (RNN) has achieved 98.1 per cent recall, which is defined as the number of true meteors properly classified as meteors. The RNN allowed only 2.1 per cent leakage, defined herein as the number of false positives that were incorrectly identified as meteors. The desire is to maximize recall to avoid missed orbit estimations, while also minimizing false alarms leaking through to the next processing stage of multi-site trajectory and orbit estimation. When two-dimensional spatial imagery is available or the temporal image sequence can be reconstructed, these results climb to 99.94 per cent recall and only 0.4 per cent leakage when employing a convolutional neural network (CNN). This has been further generalized from a baseline of interleaved analog video to modern progressive scan digital imagery with equivalent results. The trained CNN, nicknamed MeteorNet, will be used for post-detection automated screening of potential meteor tracks and explored in the future as a potential upstream meteor detector.

A Phase-Preserving Focusing Technique for TOPS Mode SAR Raw Data Based on Conventional Processing Methods

We present a new solution for the phase-preserving focusing of synthetic aperture radar (SAR) raw data acquired through the Terrain Observation with Progressive Scan (TOPS) mode. The proposed algorithm consists of a first interpolation stage of the TOPS raw data, which takes into account the Doppler Centroid frequency variations due to the azimuth antenna steering function, and allows us to unfold the azimuth spectra of the TOPS raw data. Subsequently, the interpolated signals are processed by using conventional phase-preserving SAR focusing methods that exploit frequency domain and spectral analyses algorithms, which are extensively used to efficiently process Stripmap and ScanSAR data. Accordingly, the developed focusing approach is easy to implement. In particular, the presented focusing approach exploits one of the available frequency domain Stripmap processing techniques. The only modification is represented by the inclusion, within the 2D frequency domain focusing step, of a spurious azimuth chirp signal with a properly selected azimuthal rate. This allows us to efficiently carry out the TOPS azimuth focusing through the SPECAN method. Furthermore, an important aspect of this algorithm is the possibility to easily achieve a constant and tunable output azimuth pixel size without any additional computing time; this is a remarkable feature with respect to the full-aperture TOPS-mode algorithms available in the existing literature. Moreover, although tailored on Sentinel-1 (S1) raw data, the proposed algorithm can be easily extended to process data collected through the TOPS mode by different radar sensors. The presented experimental results have been obtained by processing real Sentinel-1 raw data and confirm the effectiveness of the proposed algorithm.

An enhanced pose tracking method using progressive scan matching

Purpose The purpose of this paper is to propose an enhanced pose tracking method using progressive scan matching, focusing on accuracy, time efficiency and robustness. Design/methodology/approach The general purpose of localization algorithms is to dynamically track a robot instead of globally locating one. In this paper, progressive scan matching is used to promote the performance of pose tracking. Rotational and translational samples are separately generated to accelerate the calculation and to increase the accuracy. Progressive iteration of sample generation can ensure localization to achieve a specific precision. The direction of localization uncertainty is taken into consideration to increase robustness. Nonlinear optimization is adopted to achieve a more precise result. Findings The proposed method was implemented on a self-made mobile robot. Two experiments were conducted to test the accuracy and time efficiency of the method. The comparison with the basic Monte Carlo localization shows the advantages of the method. Another two experiments were conducted to test the robustness of the method. The result shows that the method can relocate a robot from an inaccurate place if the offset is moderate. Originality/value An enhanced pose tracking method is proposed to promote the performance by separately processing rotational and translational samples, progressively iterating the sample generation, taking the direction of localization uncertainty into consideration and adopting nonlinear optimization. The proposed method enables a robot to accurately and quickly locate itself in the environment with robustness.

A Bistatic Imaging Method for GEOSAR in the Strip Mode and UAVSAR in the Steering Beam Mode

The bistatic configuration with a geosynchronous orbital SAR (GEOSAR) transmitter and unmanned aerial vehicle SAR (UAVSAR) receiver can continuously image in any dangerous and interesting district. In this paper, the new imaging method in the case with the smaller orbital inclination of geosynchronous earth orbit and the steering beam working mode of UAVSAR was mainly studied and analyzed. GEOSAR can be approximately expressed as a static state, and only the receiver provides all the Doppler information. UAVSAR works in the steering beam modes, such as spotlight, sliding spotlight, and TOPS (Terrain Observation by Progressive Scan) mode. The azimuth bandwidth increased by the steering beam causes an aliasing situation in the azimuth frequency domain. To solve this problem, the proposed imaging method corrects the azimuth frequency aliasing using the scaling transform and the bulk azimuth compression. Compared with the traditional imaging method, the simulation validates perfectly the effectiveness of the bistatic imaging algorithm.

Coseismic Deformation Field of the Mw 7.3 12 November 2017 Sarpol-e Zahab (Iran) Earthquake: A Decoupling Horizon in the Northern Zagros Mountains Inferred from InSAR Observations

The study of crustal deformation fields caused by earthquakes is important for a better understanding of seismic hazard and growth of geological structures in tectonically active areas. In this study, we present, using interferometric measurements constructed from Sentinel-1 Terrain Observation with Progressive Scan (TOPS) data and ALOS-2 ScanSAR, coseismic deformation and source model of the Mw 7.3, 12 November 2017 earthquake that hit northwest of the Zagros Mountains in the region between Iran–Iraq border. This was one of the strongest seismic events to hit this region in the past century, and it resulted in an uplift area of about 3500 km2 between the High Zagros Fault (HZF) and Mountain Front Fault (MFF) with a maximum amount of 70 cm south of Miringe fault. A subsidence over an area of 1200 km2 with a maximum amount of 35 cm occurred near Vanisar village at the hanging wall of the HZF. Bayesian inversion of interferometric synthetic aperture radar (InSAR) observations suggests a source model at a depth between 14 and 20 km that is consistent with the existence of a decoupling horizon southwest edge of the northern portion of the Zagros Mountains near the MFF. Moreover, we present evidence for a number of coseismically induced rockslides and landslides, the majority of them which occurred along or close to pre-existing faults, causing decorrelation in differential interferograms. Exploiting the offset-tracking technique, we estimated surface motion by up to 34 and 10 m in horizontal and vertical directions, respectively, due to lateral spreading on a big coseismic-induced landslide near Mela-Kabod. Field observations also revealed several zones of en echelon fractures and crack zones developed along a pre-existing fault passing through Qasr-e Shirin City, which exhibited secondary surface slip by up to 14 cm along its strike.

COSEISMIC DISPLACEMENT ANALYSIS OF THE 12 NOVEMBER 2017 MW 7.3 SARPOL-E ZAHAB (IRAN) EARTHQUAKE FROM SAR INTERFEROMETRY, BURST OVERLAP INTERFEROMETRY AND OFFSET TRACKING

Interferometric wide-swath mode of Sentinel-1, which is implemented by Terrain Observation by Progressive Scan (TOPS) technique, is the main mode of SAR data acquisition in this mission. It aims at global monitoring of large areas with enhanced revisit frequency of 6 days at the expense of reduced azimuth resolution, compared to classical ScanSAR mode. TOPS technique is equipped by steering the beam from backward to forward along the heading direction for each burst, in addition to the steering along the range direction, which is the only sweeping direction in standard ScanSAR mode. This leads to difficulty in measuring along-track displacement by applying the conventional method of multi-aperture interferometry (MAI), which exploits a double difference interferometry to estimate azimuth offset. There is a possibility to solve this issue by a technique called “Burst Overlap Interferometry” which focuses on the region of burst overlap. Taking advantage of large squint angle diversity of ~1° in burst overlapped area leads to improve the accuracy of ground motion measurement especially in along-track direction. We investigate the advantage of SAR Interferometry (InSAR), burst overlap interferometry and offset tracking to investigate coseismic deformation and coseismic-induced landslide related to 12 November 2017 Mw 7.3 Sarpol-e Zahab earthquake in Iran.

“…I Just Wanted to Report Me, I Went Into the Subway Without Paying 9 Times…”

A clinical case is presented. The reason for admission was for behavioral disturbances and agitation piscomotriz episode in the street: she had gone to a library to “denounce” the police for entering the subway without paying several times. The patient was very distraught because she was heavily guarded (someone had tapped her phone, entered her house, changed objects place, she was chased down the street…). In the psychopathological examination revealed the sphere of language, her speech was fluid, with pressured speech, full of details, with loss of thread and highlighted the presence of neologisms and grammatical errors (changes of subject and predicate…) and changes some letters by others in the same word. She often used sayings incorrectly and, when you are exploring about this fact, objectively presenting alteration in abstract thinking. In addition, it presents self-references on television. The diagnostic impression was chronic psychotic process of years of evolution. In this case, it was decided to administer intramuscular antipsychotic treatment because she was not aware of the disease but presenting good tolerability profile because, otherwise, leave the track and also a good social functioning was sought. Currently, she continues in mental health, she has not reported new crisis and a progressive scan objective improvement in the organization of thought and speech, leaving the psychotic symptoms.Disclosure of interestThe authors have not supplied their declaration of competing interest.