1,967 research outputs found
Variability and uncertainty in measuring sea surface temperature
No full textSea Surface Temperature (SST) measurement is one of the most easily obtainable climate variables. However, it is challenging to meet the required absolute accuracy and long term stability whether the data are derived by in situ or satellite measurements. This study explores the quality of SST measurements, in particular those derived by the Advanced Along Track Scanning Radiometer (AATSR) and in situ measurements recorded by the shipborne Infrared Sea surface temperature Autonomous Radiometer (ISAR), which are used for validating AATSR data. Its broad objective is to improve understanding of measurement uncertainties in order to quantify the quality of satellite derived SST used for climate records.The uncertainties of in situ measurement by ISAR have been analysed and modelled in order to estimate an independent measurement uncertainty for every SST data point in the ISAR records. In a complementary study the separate uncertainties of the SST as observed by AATSR, ISAR and ship-based hull-mounted thermometry (SSTdepth), when observing the same track, have been resolved by means of three way uncertainty analysis. This not only serves to verify the ISAR uncertainty model but also demonstrates the effectiveness of using shipborne radiometry in preference to in water thermometry from ships or buoys for validating satellite SST products. A third area of study concerns the errors and uncertainties when comparing satellite and in situ observations, which result from failure to properly match the in situ observations to what the satellite sees". A new method has been developed for classifying the match-up quality" of each data pair. Its use is demonstrated to show that the quality of AATSR data may be better than classical validation match
Developments in target micro-doppler signatures analysis: radar imaging, ultrasound and through-the-wall radar
No full textTarget motions, other than the main bulk translation of the target, induce Doppler modulations around the main Doppler shift that form what is commonly called a target micro-Doppler signature. Radar micro-Doppler signatures are generally both target and action speci c and hence can be used to classify and recognise targets as well as to identify possible threats. In recent years, research into the use of micro-Doppler signatures for target classi cation to address many defence and security challenges has been of increasing interest. In this paper, we present a review of the work published in the last 10 years on emerging applications of radar target analysis using micro-Doppler signatures. Speci cally we review micro-Doppler target signatures in bistatic SAR and ISAR, through-the-wall radar and ultrasound radar. This article has been compiled to provide radar practitioners with a unique reference source covering the latest developments in micro-Doppler analysis, extraction and mitigation techniques. The paper shows that this research area is highly active and fast moving and demonstrates that micro-Doppler techniques can provide important solutions to many radar target classification challenges
Wide-band multi-look passive ISAR
No full textThis chapter discusses the passive inverse synthetic aperture radar (SAR) (ISAR) (P-ISAR) technique. Radar imaging, and in particular P-ISAR, is a new feature for passive radars (PRs) made possible by the recent technological advances. This chapter presents the theory of the P-ISAR algorithm. It also discusses the issues related to the application of the ISAR technique to passive coherent location (PCL) systems and in particular the obtainable spatial resolutions. How to deal with this problem is also discussed in this chapter. Finally, results on real data from two different PCL systems are presented to demonstrate the feasibility and effectiveness of P-ISAR. This chapter is organized as follows. Section 4.1 introduces the P-ISAR concepts and its main ‘ingredients’. Section 4.2 deals with the data preprocessing that includes all the steps necessary to obtain data suitable for the application of ISAR technique. Section 4.3 presents the ISAR image processing algorithm. It also proposes a method for handling incomplete data, particularly data with frequency ranges, that occurs when a full bandwidth signal is not available. Section 4.4 presents the results obtained by processing two datasets gathered with two different PCL systems. Main conclusions are finally drawn in Section 4.5. Chapter Contents: • 4.1 Introduction • 4.2 Data pre-processing • 4.2.1 Target extraction • 4.2.2 Merging of RD maps and ISAR data formation • 4.3 ISAR image processing • 4.3.1 Conventional ISAR imaging • 4.3.2 CS-based ISAR imaging • 4.4 Results • 4.4.1 Cooperative targets - WUT system • 4.4.1.1 Passive-ISAR imaging results: Astice • 4.4.1.2 Passive-ISAR imaging results: P92 • 4.4.2 Non-cooperative targets - SMARP • 4.5 Conclusions • References.</p
STAP-ISAR
No full textThe aim of this chapter is to develop a processing chain that exploits multichannel information provided by a multichannel synthetic aperture radar (SAR) system to obtain high-resolution images of noncooperative moving target within SAR images. There are two steps of the proposed processing chain. Clutter suppression and platform motion compensation are first performed through the space-time adaptive processing (STAP) processing by exploiting the multichannel information in order to improve target detection capability within SAR image. At this point, inverse synthetic aperture radar (ISAR) autofocusing is required in order to compensate the residual target own motion and to reduce the defocusing effect due to that unknown motion component. The study of moving target detector (MTD)/Moving Target Indicator (MTI) techniques and the development of clutter mitigation algorithms are the aims of this chapter together with the study of the applicability of ISAR processing to refocus moving target detected within SAR images. The integration of the proposed algorithms with ISAR techniques leads to the final processing chain. All the developed techniques are tested on simulated and real dataset. Chapter Contents: • 3.1 Mathematical background • 3.1.1 Multichannel ISAR signal model • 3.1.2 High-resolution imaging of noncooperative moving targets • 3.1.2.1 ISAR processing • 3.1.3 Clutter model • 3.2 Space-time adaptive processing for clutter suppression • 3.2.1 Joint SDAP ISAR • 3.2.1.1 Optimum processing • 3.2.1.2 Suboptimum processing • 3.2.2 Joint E-SDAP ISAR • 3.2.2.1 Optimum processing • 3.2.2.2 Suboptimum processing • 3.3 Results • 3.3.1 SDAP-ISAR results • 3.3.1.1 Dataset description • 3.3.1.2 Multichannel range-Doppler image formation • 3.3.1.3 Clutter suppression and imaging • 3.3.2 E-SDAP ISAR results • 3.3.2.1 Dataset description • 3.3.2.2 Multichannel range-Doppler image formation • 3.3.2.3 Clutter suppression and imaging • 3.4 Conclusion • References.</p
Multi-channel P-ISAR grating lobes cancellation
No full textThe coherent combination of multiple channels for ISAR imaging purposes in passive radar systems is required in order to achieve a good range resolution. Passive ISAR may provides a suitable means to implement automatic target classification (ATC) and automatic target recognition (ATR). The range resolution is related to the transmitted signal bandwidth, therefore adjacent and non adjacent multi-channel signals should be exploited to obtain a wide band signal. This paper addresses the grating lobes issue that rises when a wide band signal with bandwidth gaps is obtained by adjoining multiple adjacent DVB-T channels. A cancellation technique based on the spatially variant apodization (SVA) technique is proposed. Results both on simulated and real data are provided.</p
고속 ISAR 움직임 보상 알고리즘 및 탐색레이더 시스템에서의 ISAR 영상 형성 기법
No full text학위논문(박사) - 한국과학기술원 : 전기및전자공학부, 2020.8,[iv, 69 p. :]Along with high resolution range profile (HRRP) and jet engine modulation (JEM) signals, inverse synthetic aperture radar (ISAR) images are widely used in radar target recognition. A motion compensation process is essential for ISAR image acquisition, but this compensation process takes a long time. In addition, ISAR images can be currently obtained from the tracking radar. It is necessary to expand the image acquisition technique to a search radar that is widely used compared to a tracking radar. In this thesis, the author proposes an algorithm that solves the shortcomings of the processing time of the existing motion compensation process, and also an algorithm that acquires ISAR images from discontinuous and insufficient received signals of a search radar.
The fast motion compensation algorithm is divided into two parts: the rough optimization and the precise optimization. In the rough optimization process, the entropy envelope value is used as the fitness function instead of the entropy used as the fitness function in the existing SSA algorithm. Using a small number of phase samples, it is possible to quickly reach the point where the entropy is minimum. Since the proposed algorithm significantly reduces the number of phase samples, the processing time of the motion compensation process can also be significantly reduced. The performance of the proposed algorithm was evaluated from the received signal obtained through simulation and measurement, and it was confirmed that the processing time of the proposed algorithm is reduced by 8.7 times compared to the existing algorithm. Therefore, real-time ISAR image acquisition is possible using the proposed algorithm.
In the proposed algorithm for ISAR image acquisition in search radar, it is essential to reconstruct the received signal in the time domain that the search radar cannot observe. In the received signal in the visible region, information of scattering centers is obtained using a scattering center extraction technique, and the received signal in the invisible region is reconstructed using the information. The reconstructed signal has a similarity to that of the tracking radar, and if it is compensated using the ISAR motion compensation algorithm, it is possible to acquire the ISAR image from the search radar. The simulation showed that it is possible to acquire ISAR images from the received signal of the search radar.한국과학기술원 :전기및전자공학부
CLEAN technique for polarimetric ISAR
No full textThis paper addresses the problem of estimating the position and the scattering vector of target scattering centres from polarimetric ISAR images. The proposed technique is obtained by extending the CLEAN technique, which was introduced in radar imaging for extracting scattering centres from single polarisation ISAR images.</p
CLEAN technique for polarimetric ISAR
No full textThis paper addresses the problem of estimating the position and the scattering vector of target scattering centres from polarimetric ISAR images. The proposed technique is obtained by extending the CLEAN technique, which was introduced in radar imaging for extracting scattering centres from single polarisation ISAR images.</p
Identification of Seniors at Risk (ISAR) in the emergency room: a prospective study
No full textIntroduction: The Identification of Seniors at Risk (ISAR) is one of the most frequently utilized risk screening
tools in emergency departments (ED). The goal of this study was to evaluate the predictive validity of
the ISAR screening tool for adverse outcomes in an ED.
Methods: This was a prospective single-center observational study in a Portuguese urban university hospital
ED, and included 402 older adults (OA). After triage, baseline sociodemographic and clinic data were
collected by the researcher and the ISAR was administered. Baseline ISAR, adverse outcomes (ED revisits
and hospital admission) at 30 (early) and 180 (late) days were evaluated.
Results: ISAR screening showed that 308 (76.62%) OAs were at risk (cutoff 2). High-risk patients were
more like to be older, take more medication, have urgent or very urgent ED visits and have longer ED
lengths of stay. The high-risk group were more likely to demonstrate both early (OR = 2.43, 95% CI
1.35–4.35, p < 0.01) and late returns to the ED (AO = 1.70, 95% CI 1.04–2.79, p < 0.05). The ISAR did not
predict any significant variable for hospital admission in 30 or 180 days.
Discussion: The ISAR predicted returns to EDs at 30 and 180 days for OAs at risk, but was unable to predict
early or late hospital readmission
Application of optimal sensor positioning to bistatic ISAR
No full textBistatic ISAR (B-ISAR) imaging has recently been considered to overcome some limitations of monostatic ISAR systems. The target projection on the ISAR image plane depends on the target's own motions and on the relative position of target transmitter and receiver. Although the target's own motion cannot be controlled by the radar, the relative tx-Target-rx positions can be somehow controlled or predicted in some cases. In this paper, the theoretical aspects of optimal sensor positioning for obtaining desired B-ISAR image projections are detailed. Results are then applied to B-ISAR in a maritime surveillance scenario.</p
- …
