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em710 manualPlease enable JavaScript and reload the page. Currently the following systems are supported: EM-2040 EM-2040C EM-2040M EM-2040P EM-710 EM-712 EM-302 EM-122 For raw data processing the driver can optionally store raw bathymetry and seabed image records in the Qinsy database. Warning This drivers manual is for Qinsy version 8.15.1 and upward. If you have an older Qinsy version, please use the Drivers Manual from the Qinsy Console. The Clock datagram contains the serial number of the main head; this is always the first, port head. If the second head is to be decoded then the driver will decode the datagram with the serial number not equal to the main serial number. It is equal to the scaled standard deviation of the range divided by the detected range. Smaller means better quality. The decode Intensity stands for the backscatter reflectivity in dB. The Runtime messages are only decoded for the raw data storage and are not decoded any further. They are stored as normal footprints. If you use a single head setup, there is no need to use the Data Distribution program Kongsberg has. Note that there is a fixed port and that you can select in SIS which data needs to be send via that port: At least the N, Y, C, k datagrams should be selected. The output port number as entered in SIS will have to be entered as the driver network port. We have seen problems where packets were dropped. This can be solved by changing the power plan on the HWS pc from 'Balanced' to 'High Performance' when using a Windows7 pc. This will minimize the chances of any dropped packets. Preferably no programs that re-send the network packets such as Kongsberg DataDistrib are to be used. This is no longer necessary since multiple heads can now be decoded in one Qinsy driver executable. This can be solved by changing the power plan on the HWS pc from 'Balanced' to 'High Performance' when using a Windows7 pc. These external sensors will have to be interfaced directly to Qinsy as well.http://www.feuerwehr-adlitz.de/images/uploadedimages/dell-s1909wx-manual.xml
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However, all combinations are possible. Note that for the sake of simplicity of usage in Qinsy it is by far the easiest to mount the transducers with normal, non-reversed, orientation.Bow, starboard and up are positive. The x,y,z positions for the RX and TX transducer arrays are relative to the center of the sonar head face. See figure 'EM2040C Reference point, the so-called face of the center of the transducer' on this page. The x,y,z positions of the RX line array are relative to the center of the sonar head face. The x,y,z positions of the RX line array are relative to the centre of the sonar head face.The transducer arrays are not placed at the center of the sonar head. The EM 2040C can have one or two sonar heads. For most EM echo sounders separate x,y,z installation parameters are given for the RX and the TX arrays. For EM 2040C the installation parameters entered by the operator refers to the centre of the face of the sonar head(s). The transducer arrays are not placed at the center of the sonar head. For most EM echosounders separate x,y,z installation parameters are given for the RX and the TX arrays. For EM 2040P the installation parameters entered by the operator refers to a reference point on the face of the sonar head. This point is not marked on the sonar head. The reference point used is the intersection between two diagonal lines drawn between the bumpers on the sonar head face. This will make sure that both heads are handled by one driver executable. This program comes with SIS. For a dual head the program needs to be used. See ' How-to Kongsberg Multibeam - Reference Position ' The STORAGE of the water column is activated with a setting in the Controller's Session Setup - Database page. These should therefore be entered separately. This explains in more detail how to carry out a calibration. We have seen problems where packets were dropped.http://sns-russia.ru/userfiles/dell-s2209w-user-manual.xml This can be solved by changing the power plan on the HWS pc from 'Balanced' to 'High Performance' when using a Windows7 pc. The raw seabed data is now part of the multibeam data. The port and starboard beams may be reversed then and a height offset may occur. The seller has relisted this item or one like this. Learn more - opens in a new window or tab This amount is subject to change until you make payment. For additional information, see the Global Shipping Programme terms and conditions - opens in a new window or tab This amount is subject to change until you make payment. If you reside in an EU member state besides UK, import VAT on this purchase is not recoverable. For additional information, see the Global Shipping Programme terms and conditions - opens in a new window or tab Learn More - opens in a new window or tab Learn More - opens in a new window or tab Learn More - opens in a new window or tab Learn More - opens in a new window or tab Learn More - opens in a new window or tab The item may have some signs of cosmetic wear, but is fully operational and functions as intended. This item may be a floor model or an item that has been returned to the seller after a period of use. See the seller’s listing for full details and description of any imperfections. Contact the seller - opens in a new window or tab and request post to your location. Please enter a valid postcode. Please enter a number less than or equal to 1. Some specific purchases aren't covered by eBay Money Back Guarantee Learn more eBay Money Back Guarantee disclaimer - opens in a new window or tab. All Rights Reserved. User Agreement, Privacy, Cookies and AdChoice Norton Secured - powered by Verisign. Please upgrade your browser or activate Google Chrome Frame to improve your experience.http://www.raumboerse-luzern.ch/mieten/boss-gt-6-manual-espa-ol-pdf As a Mac Tools franchisee you can be your own boss and fulfill your dream of starting your own business, whilst receiving the full support of the Mac Tools franchise team This library of latest press releases contains information such as company news, product developments, awards and sponsorship partnerships Mac Tools use only the most innovative manufacturing to create the highest quality toolsThis same spirit has made Mac Tools a world leader in the automotive tool and equipment business today.This library of latest press releases contains information such as company news, product developments, awards and sponsorship partnerships. PostscriptHysweep HSX data (format 201), including applying time lag and biases toOutput some basic statistics of segy seismic data files. PostscriptSwathPlus SXP data (format 222), including applying time lag and biases toReson 7k data (format 88), including applying time lag and biases toMB-System and other software packages to accomplish common tasksThese are the current MB-System macros:Translate an mbgrdviz survey route file into an MBARI AUV missionUTM projections. Learn more - opens in a new window or tab This amount is subject to change until you make payment. For additional information, see the Global Shipping Programme terms and conditions - opens in a new window or tab Delivery times may vary, especially during peak periods and will depend on when your payment clears - opens in a new window or tab. Learn More - opens in a new window or tab Learn More - opens in a new window or tab Learn More - opens in a new window or tab Learn More - opens in a new window or tab Learn More - opens in a new window or tab The item may have some signs of cosmetic wear, but is fully This item may be a floor model or an item that has been returned to the seller after a period of use. See the seller’s listing for full details and description of any imperfections.http://atmos-service.com/images/95-saturn-manual.pdf Contact the seller - opens in a new window or tab and request a postage method to your location. Please enter a valid postcode. Please enter a number less than or equal to 1. Sellers may be required to accept returns for items that are not as described. Learn more about your rights as a buyer. - opens in a new window or tab You're covered by the eBay Money Back Guarantee if you receive an item that is not as described in the listing. We may receive commission if your application for credit is successful. Terms and conditions apply. Subject to credit approval. We may receive commission if your application for credit is successful. All Rights Reserved. Something went wrong. View cart for details.User Agreement, Privacy, Cookies and AdChoice Norton Secured - powered by Verisign. Next Article in Special Issue Analytical Approximation Model for Quadratic Phase Error Introduced by Orbit Determination Errors in Real-Time Spaceborne SAR Imaging Previous Article in Special Issue A Gray Scale Correction Method for Side-Scan Sonar Images Based on Retinex Please note that many of the page functionalities won't work as expected without javascript enabled.The ( a ) and ( c ) are SSS and MBES image; red rectangles in ( a ) and ( c ) are the locations of the feature points; ( b ) and ( d ) are LSS descriptors of the two points. The colored full lines in ( a ) ( b ) ( c ) ( b1 ) and ( c1 ) are used to connect matched points. The red dotted rectangles in ( a ) ( b ) ( c ) are the segmented blocks. The black rectangles in ( b ) and ( c ) are the zoomed areas ( b1 ) and ( c1 ). The red rectangle in ( b1 ) shows the several-to-one matching phenomena. The colored full lines in ( a ) ( b ) ( c ) ( b1 ) and ( c1) are used to connect matched points. The red rectangles in ( a ) ( b ) ( c ) are the segmented blocks. The black rectangles in ( b ) and ( c ) are the zoomed areas ( b1 ) and ( c1 ). The ( a1 ) and ( b1 ) are the zoomed areas; ( c ) is the example with sharper edges; the colored full lines in ( a ) ( b ) and ( c ) are used to connect matched points. Multibeam echo sounder (MBES), which can simultaneously obtain high-accuracy seabed topography as well as seabed images with low resolution in deep water. Based on the complementarity of SSS and MBES data, this paper proposes a new method for acquiring high-resolution seabed topography and surface details that are difficult to obtain using MBES or SSS alone. Firstly, according to the common seabed features presented in both images, the Speeded-Up Robust Features (SURF) algorithm, with the constraint of image geographic coordinates, is adopted for initial image matching. Secondly, to further improve the matching performance, a template matching strategy using the dense local self-similarity (DLSS) descriptor is adopted according to the self-similarities within these two images. Next, the random sample consensus (RANSAC) algorithm is used for removing the mismatches and the SSS backscatter image geographic coordinates are rectified by the transformation model established based on the correct matched points. Finally, the superimposition of this rectified SSS backscatter image on MBES seabed topography is performed and the high-resolution and high-accuracy seabed topography and surface details can be obtained.This kind of operation can minimize the effects of platform movements on the SSS backscatter images. By using the Ultra Short Base Line (USBL) or Short Base Line (SBL) in the surveying process, the accuracy of towfish positions can be improved. However, these two devices are not used in most cases because of high cost. The output from 3DSS is in the form of an intensity point cloud, which can be post-processed either as bathymetry, backscatter seabed image or a combination of both. MBES is designed for high-accuracy bathymetric work and modern MBES can receive hundreds of echoes from the seabed for one ping and provide a highly detailed backscatter image simultaneously. The MBES is usually installed on a surveying vessel ( Figure 1 b). Although it can be used for large-scale bathymetric measurement, the interval of footprints in a ping will be enlarged and the bathymetric resolution will be decreased as the water depth and beam incident angle grow. The central point of a beam is optimally positioned with minimal geometric distortions and the image pixels are distributed around it. The complementarity of SSS and MBES data provides a way to obtain detailed seabed features by superposing a two-dimensional (2D) SSS backscatter image onto 3D MBES bathymetric terrain. However, because SSS backscatter image geographic coordinates are inaccurate, it is a challenge to conduct the superimposition of these two categories of data directly. Much research has been carried out in this field. The two methods need sufficient topological variations on the seafloor for creating distinct edges or feature points in sonar images and may fail when dealing with a flat seabed with various sediments. This method can improve matching performance but its results depend heavily on the seabed classification accuracy. The above methods ignore the imaging mechanism differences between SSS and MBES images, which often lead to inaccurate descriptions of the feature points and result in inaccurate image matching. Considering the limitations of the existing methods, this paper proposes a new SSS and MBES image matching method for acquiring high-resolution and high-accuracy seabed topography and surface details, which can overcome the limitations of adopting a single MBES or SSS for seabed mapping. The remainder of this paper is organized as follows: Section 2 describes the superimposition method in detail; Section 3 designs the experiments to verify the proposed method; Section 4 analyzes the results; Section 5 discusses the proposed method; and Section 6 presents the conclusions according to the experiments and discussions. 2. Method To get high-resolution seabed topography and surface backscatter data, the proposed method is shown in Figure 2. Firstly, both SSS and MBES data are processed to form the geocoded images. Secondly, the SSS and MBES image matching based on common features is conducted, which includes the initial matching with the SURF algorithm with image geographic coordinate constraint and finer matching by using dense local self-similarity (DLSS) descriptors. Thirdly, the random sample consensus (RANSAC) algorithm is used for removing mismatches and then the SSS backscatter image geographic coordinates are rectified according to the relationship model established by the correct matched points. Finally, according to the consistent geographic coordinates, the rectified SSS backscatter image is superposed on the MBES bathymetric terrain. The proposed method is described in detail in the following paragraphs and the image matching program was written using Matlab in a computer with the i7, 3.40GHz Intel Core and 8.00 GB RAM. 2.1. SSS and MBES Data Processing The original SSS data were first decoded to form waterfall images ping by ping. This SSS data processing was conducted by self-developed software and the processing procedure is shown in Figure 3 a. Because thousands of echoes exist in a ping scanning line, a high-resolution SSS backscatter image could be obtained after the above data processing. By referring to Figure 1 a, the positions of SSS towfish were reckoned by combining vessel-mounted GPS positioning results, cable length and the towfish heading, and thus became inaccurate due to the towing operation, the flat bottom assumption, towing distance and bearing controlled by the towing speed and the currents. Therefore, the geographic coordinates of high-resolution SSS backscatter image needed to be rectified. The original MBES data were first decoded to get the bathymetric data, backscatter data, GPS data, attitude data, sound velocity, and so forth. Quality control for these raw data was done first. Then, calculation of bathymetric point was conducted which includes attitude correction, sound ray tracing, absolute coordinates obtaining of bathymetric point, and so forth. After getting the locations of beam footprints, the authors conducted the radiometric correction, angular response correction and geocoding for the MBES backscatter data, and could then obtain the seabed image. Finally, after tidal correction for the sound ray tracing results, the absolute 3D coordinates of each bathymetric point were obtained and thus the seabed topography could be achieved. The procedure of MBES backscatter and bathymetric data processing was displayed in Figure 3 b. To avoid gaps on the MBES image, the survey vessel velocity should be determined appropriately. According to the MBES data processing procedure and MBES measurement principle ( Figure 1 b), the geographic coordinates of bathymetric and backscatter data were accurate. However, the seabed topography and image obtained by using MBES were of low resolution, as only hundreds of echoes exist in one ping. As for the MBES backscatter, there were three types of acquired data: single beam intensity, individual beam time series and integrated time series. Although there exist a few to dozens of snippets in each beam footprint, the resolution of MBES image was still far lower than that of the SSS backscatter image. Thus, the MBES image is usually used for reflecting the large-scale seabed surface features instead of high-resolution visualization. 2.2. SSS and MBES Image Matching Though with different characteristics (e. g. resolution, position accuracy and intensity contrast), both SSS and MBES images can reflect seabed features of the same area. Thus, the SSS and MBES image matching can be conducted by searching for common features in both images. To get accurate matched points, the matching method is proposed, which includes initial matching using the SURF algorithm with image geographic coordinate constraint, and the finer matching by using dense local self-similarity (DLSS) descriptors. The initial image matching step is to detect image feature points in the first place and use the SURF descriptors for feature-based image matching with the constraint of image coordinates. Since the SURF algorithm is not robust to nonlinear intensity differences between SSS and MBES images, some mismatches may arise in the initial matching step. To obtain more accurate matched points, the DLSS descriptor was used in the finer matching step and a template matching strategy was adopted.For geocoded SSS and MBES images, the accuracies of their geographic coordinates are different and the geographic coordinates of the MBES image are more accurate than those of SSS because the SSS surveying is easily affected by the towing operation and many other factors. This inconsistency of image positional accuracy leads to the fact that the geographic coordinates of the same features presented in both images will be different. This kind of difference is within a range and can be determined by SSS location error, which is discussed in detail in Section 5.1. Thus, when the distances of the detected feature points in both images are too large, they will certainly not be the correct matches. Accordingly, the SURF algorithm for SSS and MBES image matching can be conducted when the distances of detected feature points in both images are within a threshold Dis, which can reduce the mismatches compared with using the SURF algorithm directly. With this constraint, the initial feature-based image matching was conducted as shown in Equation (2).The determination of threshold Dis is also described in detail in Section 5.1. 2.2.2. Finer Image Matching Using DLSS Descriptors Because the SSS backscatter reflects relative backscatter levels and the MBES images are usually normalized to dB scale, there is no linear relationship between their backscatter intensity levels. Meanwhile, as the resolution, SNR and intensity contrast of SSS backscatter image are higher than those of the MBES image, the same feature points of the seabed may be presented more clearly in SSS backscatter image than in the MBES image. As a result, some feature points can be detected in the SSS backscatter image but not in the MBES image. Moreover, as the number of detected feature points in the two images were different, the finally obtained number of matched points was limited. To get better matched points, the shape properties of distinct targets, topography changes or sediment distributions in these images can be used.Then, the S q ( x,y ) was transformed into a log-polar representation and partitioned into bins. The maximal correction value of each bin was selected to generate the LSS descriptor associated with the pixel q. An example of the LSS descriptor is shown in Figure 4, which indicates that the LSS descriptors of feature points are similar when the points share a common layout. Using the DLSS descriptors, a template matching strategy was conducted based on the initial image matching results. First, the DLSS descriptors of initial matched points in the SSS backscatter image were produced and a searching area centered at the initial matched points in the MBES image with the radius r was defined. Meanwhile, the DLSS descriptors of every pixel in this defined area were calculated. Secondly, calculating the similarity between the DLSS descriptors of the SSS backscatter image feature points and those of the points still unprocessed in the above defined searching area in the MBES image. The normalized cross correlation (NCC) of DLSS descriptors as shown in Equation (4) was adopted as the similarity metric.Finally, by choosing maximum NCCs and selecting the corresponding points in the defined area of the MBES image, the finer matches could be obtained. After conducting the above process for all the initial matched points in the SSS backscatter and MBES images, more correct matched points were obtained. 2.3. SSS Backscatter Image Geographic Coordinates Rectification Based on the Matched Points Even after the finer matching step, mismatches still existed. The reason is that, affected by the measurement environment (e.g., the currents, the surveying vessel velocity and attitude changes), the seabed features presented in the SSS and MEBS images may not be identical. To eliminate these mismatches, the random sample consensus (RANSAC) algorithm was adopted. Meanwhile, to ensure the continuity between adjacent blocks, an overlapping ratio (e.g., one seventh of the block) can be set between them. To further ensure the remaining matches were correct, a geometric transformation model was established by using the matched points after application of the RANSAC algorithm and the coordinates of feature points in the SSS backscatter image were rectified. By referring to the matched feature points in the MBES image, the corresponding feature points in the rectified SSS backscatter image were considered as correct matches when their coordinate errors were less than double standard deviations. After this process, the correct matched points were obtained. Based on the correct matched points between SSS and MBES images in each block, a geometric transformation model could be built to rectify the geographic coordinates of the SSS backscatter image by referring to those of the MBES image.After obtaining the geometric transformation models within each segmented block, the SSS backscatter image geographic coordinates could be rectified. 2.4. Superimposition of Rectified SSS Backscatter Image on MBES Terrain After the rectification, the geographic coordinates of the SSS backscatter image were inconsistent with those of MBES image. Thus, the rectified SSS backscatter image could be superposed on the MBES terrain. This process was conducted by following steps: (1) Based on the matched points, the geographic coordinates of the SSS backscatter image were rectified by referring to those of the MBES image. (2) The 3D seabed topography was obtained by using the regular square grid method, which has the same resolution as the SSS backscatter image. (3) According to the geographic coordinates, each grid point of the 3D topography was attributed with the corresponding grey value of SSS backscatter image. After this process, the high-resolution 3D seabed topography and surface details can be presented together. 3. Experiments and Results 3.1. Experimental Data To validate the proposed method, an experiment was carried out in Meizhou Bay, China with the area of 1.4 ? 0.3 km. In this water area, the depth ranges from 10 to 14 m; seabed sampling showed sediments mainly contain silt and sand. In this experiment, EdgeTech 4100P with the slant range of 112 m and 7502 sampling points for each ping was adopted for the SSS measurement. The processing of SSS and MBES data is shown in Figure 3. Considering the sensitivity of geographical data, the coordinates have been subtracted by a constant. Meanwhile, the MBES and SSS backscatter images and the MBES topography were resampled in the same ground sample distance (GSD) of 1m. Even with the same GSD, the SSS backscatter image could reflect clearer contours of seabed surface features because there exist many more sampling points for one ping of the SSS measurement than that of the MBES measurement. For example, the pipeline is presented more clearly in the SSS backscatter image than in the MBES image. Meanwhile, the topography shown in Figure 5 c mainly reflects the 3D seabed undulations but with less detail. Thus, the superimposition of the high-resolution SSS backscatter image on high-accuracy seabed terrain can take advantage of both datasets, which can capture both the 3D seabed topography and the detailed surface features together. 3.2. Experimental Procedure and Results According to the proposed method depicted in Section 2, the SURF algorithm was first used for detecting feature points in SSS and MBES images. In a unified geographical framework, the image geographic coordinates can serve as the constraint in the initial image matching step as described in Section 2.2.1. This matching result is shown in Figure 6 b. Compared with the matching results shown in Figure 6 a, which were obtained by the classical SURF algorithm without constraint, the initial matching result with constraint seems better. The reason is that the SURF algorithm is not robust when dealing with the nonlinear intensity difference between SSS and MBES images. Meanwhile, the features existed on the seabed are relatively simple and the detected edge and point features can be represented by similar SURF descriptors, which may decrease the distinctiveness of SURF descriptors. Because of the two factors, even when two feature points in the SSS and MBES images are distant, they may be regarded as matches when they are represented by similar SURF descriptors. When using the image geographic coordinates as constraint in the initial matching step, the initial image matching is only conducted within a valid distance, which avoids mismatches when the geographic coordinates of two feature points are too far away. Moreover, since there are many more sampling points for SSS measurement than for MBES measurement, the seabed features in the MBES image may not be as clear as those in the SSS backscatter image. As a result, some feature points may be detected in the SSS backscatter image but cannot be presented in the MBES image. Consequently, it was found that several detected feature points in the SSS backscatter image are matched to one feature point in the MBES image, particularly in zoomed area (b1) of Figure 6 b. This several-to-one matching problem is obviously incorrect, which will be settled in the finer image matching step. As image geographic coordinates are used as a constraint in the initial image matching step, the correct matched points in the MBES image are supposed to be located within an area centered at the initial matched ones. Thus, the optimization search operation described in Section 2.2.2 was conducted and the better matched points are shown in Figure 6 c. In this process, a template matching strategy using DLSS descriptors was conducted. Compared with the SURF descriptor, the DLSS descriptor is robust to the nonlinear intensity difference between SSS and MBES images because it reflects the shape properties of feature points and their surrounding areas. Meanwhile, this finer image matching using a template matching strategy can also help find the same number of feature points in the MBES image as these in the SSS backscatter image.