This paper addresses the use of a data analysis tool, known as robust principal component analysis (RPCA), in the context of change detection (CD) in ultrawideband (UWB) very high-frequency (VHF) ...synthetic aperture radar (SAR) images. The method considers image pairs of the same scene acquired at different time instants. The CD method aims to maximize the probability of detection (PD) and minimize the false alarm rate (FAR). Such aim fits into a multiobjective optimization problem, since maximizing the probability of detection generally implies an increase in the number of false alarms. In that sense, varying the RPCA regularization parameter leads to PD variation with respect to FAR, which is known as receiver operating characteristic (ROC) curve. To evaluate the proposed method, the CARABAS-II data set was considered. The experimental results show that RPCA via principal component pursuit (PCP) can provide a good trade-off between PD and FAR. A comparison between the results obtained with the proposed method and a classical CD algorithm based on the likelihood ratio test provides the pros and cons of the proposed method.
The back-propagation (BP) method consists of diffractive integrals computed over a trajectory path, projecting a signal to different planes. It unwinds the diffraction and multipath, resulting in ...minimum disturbance to the BP amplitude when the auxiliary plane coincides with the region causing the diffraction. The method has been previously applied in global navigation satellite system (GNSS) radio occultation (RO) measurements to estimate the location of ionospheric irregularities but without complementary data to validate the estimation. In this study, the BP method is applied to a Communications/Navigation Outage Forecasting System (C/NOFS) occultation event containing scintillation signatures caused by an equatorial plasma bubble (EPB), which was parameterized with the aid of collocated data and reproduced in a wave optics propagator (WOP) simulation. In addition, a few more test cases were designed to assess the BP method with regard to the size, intensity, and placement of single- and multiple-irregularity regions. The results show a location estimate accuracy following the resolution at which the method is implemented (single bubble, reference case), whereas a bias is observed in multiple-bubble scenarios. The minimum detectable disturbance level and the estimation accuracy depend on the receiver noise level and, in the case of several bubbles, on the distance between them. These remarks provide insight into the BP results for two Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC) occultation events.
Global Navigation Satellite System (GNSS) Radio Occultation (RO) has provided high-quality atmospheric data assimilated in Numerical Weather Prediction (NWP) models and climatology studies for more ...than 20 years. In the satellite–satellite GNSS-RO geometry, the measurements are susceptible to ionospheric scintillation depending on the solar and geomagnetic activity, seasons, geographical location and local time. This study investigates the application of the Support Vector Machine (SVM) algorithm in developing an automatic detection model of F-layer scintillation in GNSS-RO measurements using power spectral density (PSD). The model is intended for future analyses on the influence of space weather and solar activity on RO data products over long time periods. A novel data set of occultations is used to train the SVM algorithm. The data set is composed of events at low latitudes on 15–20 March 2015 (St. Patrick’s Day geomagnetic storm, high solar flux) and 14–19 May 2018 (quiet period, low solar flux). A few conditional criteria were first applied to a total of 5340 occultations to define a set of 858 scintillation candidates. Models were trained with scintillation indices and PSDs as training features and were either linear or Gaussian kernel. The investigations also show that besides the intensity PSD, the (excess) phase PSD has a positive contribution in increasing the detection of true positives.
This paper presents an iterative change detection (CD) method based on Bayes' theorem for very high-frequency (VHF) ultra-wideband (UWB) SAR images considering commonly used clutter-plus-noise ...statistical models. The proposed detection technique uses the information of the detected changes to iteratively update the data and distribution information, obtaining more accurate clutter-plus-noise statistics resulting in false alarm reduction. The Bivariate Rayleigh and Bivariate Gaussian distributions are investigated as candidates to model the clutter-plus-noise, and the Anderson-Darling goodness-of-fit test is used to investigate three scenarios of interest. Different aspects related to the distributions are discussed, the observed mismatches are analyzed, and the impact of the distribution chosen for the proposed iterative change detection method is analyzed. Finally, the proposed iterative method performance is assessed in terms of the probability of detection and false alarm rate and compared with other competitive solutions. The experimental evaluation uses data from real measurements obtained using the CARABAS II SAR system. Results show that the proposed iterative CD algorithm performs better than the other methods.
-This article presents Bayes' theorem for wavelength-resolution synthetic aperture radar (SAR) change detection method development. Different change detection methods can be derived using Bayes' ...theorem in combination with the target model, clutter-plus-noise model, iterative implementation, and noniterative implementation. As an example of the Bayes' theorem use for wavelength-resolution SAR change detection method development, we propose a simple change detection method with a clutter-plus-noise model and noniterative implementation. In spite of simplicity, the proposed method provides a very competitive performance in terms of probability of detection and false alarm rate. The best result was a probability of detection of 98.7% versus a false alarm rate of one per square kilometer.
The Neyman-Pearson lemma, i.e., the likelihood ratio test and its generalized version, have been used for the development of the synthetic aperture radar (SAR) change detection methods. For detecting ...changes caused by targets on the ground such as vehicles, a target model, or at least certain assumptions concerning the targets, is always required for deriving a statistical hypothesis test. Without the prior knowledge on targets, it is difficult to make any assumption. An inappropriate assumption can degrade change detection performance significantly. To avoid this technical issue, some new forms of likelihood ratio test for SAR change detection are introduced in this paper. The proposed forms are shown to be flexible. They can be utilized to develop change detection methods for different types of data, e.g., data in scalar form, data in vector form, data represented in complex number, and data represented in real number. The flexibility of the proposed forms is also shown by the capability to implement change detection methods in the iterative and non-iterative ways. For the illustration purpose, a new change detection method is developed on one of the introduced forms and tested with TanDEM-X data measured in Karlshamn, Sweden in 2016.
In this paper, a method for moving target relative speed estimation and refocusing based on synthetic aperture radar (SAR) images is derived and tested in simulation and on real data with good ...results. Furthermore, an approach on how to combine the estimation method with the refocusing method is introduced. The estimation is based on a chirp estimator that operates in the SAR image and the refocusing of the moving target is performed locally using subimages. Focusing of the moving target is achieved in the frequency domain by phase compensation, and therefore makes it even possible to handle large range cell migration in the SAR subimages. The proposed approach is tested in a simulation and also on real ultrawideband (UWB) SAR data with very good results. The estimation method works especially well in connection with low frequency (LF) UWB SAR, where the clutter is well focused and the phase of the smeared moving target signal becomes less distorted. The main limitation of the approach is target accelerations where the distortion increases with the integration time.
Automotive radars have become an important part of sensing systems in vehicles and other traffic applications due to their accuracy, compact design, and robustness under severe light and weather ...conditions. The increased use of radars in various traffic applications has given rise to the problem of mutual interference, which needs to be mitigated. In this paper, we investigate interference mitigation in chirp sequence (CS) automotive radars via signal reconstruction based on autoregressive (AR) models in fast- and slow-time. The interference is mitigated by replacing the disturbed baseband signal samples with samples predicted using the estimated AR models. Measurements from 77GHz frequency modulated continuous wave (FMCW) static and moving radars are used to evaluate the signal reconstruction performance in terms of the signal-to-interference-plus-noise ratio (SINR), peak side-lobe level (PSLL), and mean squared error (MSE). The results show that the interference is suppressed down to the general noise floor, leading to an improvement in the SINR. Additionally, enhanced side-lobe suppression is achieved via AR signal reconstruction, which is compared to a commonly used inverse-cosine method. Furthermore, the paper notes that the slow-time signal reconstruction can be more beneficial for interference suppression in certain scenarios.
Measuring supply chain cost Pettersson, Annelie I.; Segerstedt, Anders
International journal of production economics,
06/2013, Letnik:
143, Številka:
2
Journal Article
Recenzirano
Organisations focus on reducing costs in their supply chains to increase net income. In order to reduce costs a company needs to know how to measure Supply Chain Cost (SCC). This paper is concerned ...with SCC and how measurements of SCC are and can be used in industry. The paper describes a suggested model for measuring SCC. Representatives from 30 companies in 10 different business sectors are interviewed about how they measure costs in their supply chains compared against this model. The focus is also on identifying the difference between SCC based on estimated standard cost compared to actual cost. A case study describes and shows the difference between measuring SCC based on calculated standard cost and measuring it based on actual cost. Our studies show that general thorough cost and supply chain analyses in many companies can be improved and further developed.
1. In commercial free-range systems for laying hens, popholes to the outdoor range are often installed on one side of the house only. In multi-tier systems, it is possible that some individuals fail ...to access the range due to internal barriers to movement. 2. Five commercial multi-tier flocks from different units were studied. For each flock, two different colour markers were used to distinguish 200 birds roosting near the popholes (NP-Roost) and 200 birds roosting far from the popholes (FP-Roost) at night. The following day, counts of marked birds on the range and inside the house were performed. 3. Significantly more NP-Roost birds were observed in all areas of the outdoor range than FP-Roost birds the next day. Distance of FP area from the popholes was very strongly positively correlated with effect size in the adjacent range area. 4. Additionally, in the indoor area far from the popholes (FP) more FP-Roost birds were observed the next day than NP-Roost birds. In the indoor area near to the popholes (NP) more NP-Roost birds were observed the next day than FP-Roost birds. 5. These results suggest that roosting location is associated with differential range use when popholes are only available on one side of the shed as birds that roosted far from the popholes used the range less.
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