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DPT was able to detect 100% of watermark messages. Table 2 shows DPT-based technique performance for one of the images under the specified attacks. The results demonstrate the fact that the proposed scheme based on DPT-based technique promises to estimate the watermark messages up to a BER of 15%; also in many cases it shows the ability of watermark detection up to a BER of 19%. Attacks Detection Average(100%) DPT HRT Remodulation(4) 65 57.5 Copy(1) 100 97 MAP(6) 100 100 Wavelet(10) 84 84 JPEG(12) 100 97.5 ML(7) 57 56 Filtering(3) 100 100 Resampling(2) 85 90 Colour Reduce(2) 35 45 Table 1. Watermark detection results of 10 images for checkmark benchmark attacks. Attacks image1 BER(%) DPT dpr(3) 2.84 0.9988 dpr(5) 11.93 0.9954 dprcorr(3) 6.25 0.9871 dprcorr(5) 14.77 0.9916 medfilt(2) 1.7 0.9950 medfilt(3) 3.4 0.9884 medfilt(4) 23.3 0.1355 trimmedmean(3) 13.63 0.9891 trimmedmean(5) 31.82 0.1274 midpoint(3) 3.98 0.9965 midpoint(5) 23.4 -0.0008 dither 6.25 0.9936 thresh 19.31 0.9516 Table 2. Bit error rates and the correlation coefficients of the proposed method respectively. The performance of the algorithm is compared with another similar approach, Hough-Radon Transform (HRT)[3] [4][5]. Table 1 compares the detection result for DPT and HRT-based methods with the same watermarking capacity. The DPTbased algorithm results in higher or equal detection rate in the seven types of attacks, and has less computational complexity than HRT-based method. Typically, running time of DPTbased is 6000 time less than that of the HRT-based method in Matlab. The watermarking capacity of DPT-based technique 1572 45 depends on the values of coefficients a1 and a2. As expected, using high resolution of coefficients a1 and a2 will increase the capacity of the watermarking. However, this would also reduces the robustness of the method. Compared to the previous method based on HRT, the proposed method has high capacity of 182×182; it is also more robust than the HRTbased method as indicated in Table 1. 5. CONCLUSION In this paper, we proposed a watermark detection method applied in an image watermarking algorithm that embeds linear chirp as watermark messages. The watermark message is added to the perceptually significant regions of the image to ensure robustness of the watermark to common image processing attacks. A phase detection algorithm based on DPT detects the phase of the watermark message. The proposed technique has the ability to detect the chirp message embedded in signals and subjected to different BERs due to attacks on the image watermark and provides a fast deduction with high accuracy. Our studies confirm the robustness of the algorithm to checkmark benckmark attacks. 6. REFERENCES Authorized licensed use limited to: Ryerson University Library. Downloaded on July 7, 2009 at 11:25 from IEEE Xplore. Restrictions apply. [1] S. Peleg, B. Friedlander, “The discrete polynomialphase transform,” IEEE Transactions on Signal Processing, Vol. 43 Issue 8 , pp. 1901–1914. 1995. [2] S. Peleg, and B. Friedlander, “Multicomponent signal analysis using the polynomial-phase transform,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 32 Issue 1 , pp. 378–387. 1996. [3] S. Erkucuk,S. Krishnan and M. Zeytinoglu, “Robust Audio Watermarking Using a Chirp Based Technique,” IEEE Intl. Conf. on Multimedia and Expo, vol. 2, pp. 513–616, 2002. [4] A. Ramalingam and S. Krishnan, “A Novel Robust Image Watermarking Using a Chirp Based Technique,” IEEE Canadian Conf. on Electrical and Computer Engineering, vol. 4, pp. 1889–1892, 2004. [5] R.M. Rangayyan and S. Krishnan, “Feature identification in the time-frequency plane by using the Hough- Radon transform,” Trans. Pattern Recognition, vol. 34, pp. 1147–1158, 2001. [6] S. Pereira, S. Voloshynovskiy, M. Madueno S. Marchand-Maillet, and T. Pun, ‘Second Generation Benchmarking and Application Oriented Evaluation’, Information Hiding Workshop III, Pittsburgh, PA, USA, April 2001.
IMPROVING POSITION ESTIMATES FROM A STATIONARY GNSS RECEIVER USING WAVELETS AND CLUSTERING Mohammad Aram, Baice Li, Sridhar Krishnan, Alagan Anpalagan Ryerson University Multipath Mitigation (RUMM) Lab Department ofElectrical and Computer Engineering, Ryerson University, Toronto, ON, M5B 2K3 maram bli krishnan alagan@ee.ryerson.ca Bern Grush Applied Location Corporation, 34 Dodge Rd, Toronto, ON, M1N 2A 7 bgrush@appliedlocation.com Abstract Many positioning applications utilize global navigation satellite systems (GNSS) derived position estimates for stationary positions. Inexpensive navigation-grade receivers provide estimates within a few meters in relatively open skies, while more specialized devices, typically distinguished by specialized antenna design and additional post processing can achieve sub-meter accuracy. These latter devices can be two orders of magnitude more expensive than navigation-grade receivers but are still subject to measurement error due to severe multipath in built-up areas. In our experiments we post-process positions computed by an inexpensive receiver by applying waveletfilteringfollowing by clustering and characterization. This produces a reliable and significant reduction in variance of the estimate, a normalization of the data scatter-distribution and a characterization of the estimate that is amenable to a wider range of statistical comparisons and tests than would be possible for unfiltered, highly non-Gaussian distributions, especially as occur in urban canyon circumstances. Keywords. GNSS; Urban canyon; Multipath mitigation; Wavelets; k-means; RAIM 1. Introduction Ongoing developments in GNSS space segment (Galileo and GPS modernization) are poised to provide significantly more and better ranging signals for positioning applications. Recent innovation in high-sensitivity receiver technology (HSGNSS) enables the acquisition of attenuated and obstructed signals. These additional signals dramatically lower the probability of a gap [5,6,7] (loss of lock on enough signals to compute a position) in challenging signal environments such as in "urban canyon", heavy foliage, indoors, etc. While inertial navigation may fill in those gaps in dynamic applications (navigation, logistics tracking), it cannot help stationary or near-stationary applications such as survey, E9 11, asset or personnel location, or metered parking. HSGNSS signal measurements are biased and especially noisy due to excessive multipath and low-power signals [2]. Taken together, GPS modernization, Galileo and HSGNSS, means the potential opportunity of many more applications, but generally in harsh signal environments. Specific noise sources are entirely dependent on conditions local to the antenna of the 1-4244-0038-4 2006 7758 IEEE CCECE/CCGEI, Ottawa, May 2006 46 receiver in question and are not addressable by augmentation such as differential GPS (DGPS) or wide area augmentation systems (WAAS), or broad-area correction, such as atmospheric, etc. Even traditional receiver autonomous integrity monitoring (RAIM) has diminished utility since it was developed for signal environments with an assumption of zero or one fault in a field of 5 to 11 signals. We can now project near-future, integrated GPS/Galileo applications with 4 to 22 signals in harsh environments where many or all signals are disturbed. To tackle these harsher signal environments, new antenna designs [2] and new fault detection and elimination techniques (FDE) that extend RAIM approaches [6,7,8] are being developed. Specialized antennas add system costs and the FDE techniques are computationally complex so that they may be impractical for larger signal sets. This paper describes an alternate approach: a process that includes wavelet filtering, weighted clustering and characterization of position estimates from a stationary receiver. This approach results in reduced variance of the estimate and a normalization of the data-scatter which, in turn, provides an inexpensive method for applications that require accuracy of 1-2m for short-dwell readings (under ten minutes) in many multipath circumstances. As space segment improvements (Galileo, GPS modernization) and receiver design improvements (high sensitivity) continue to come onstream, multipath mitigation such as we propose here tends to reduce the relative difference in accuracy between open skies and urban canyon. The next section of this paper describes our experimental methods, including data collection and processing algorithms. The third section describes and demonstrates our results for each of wavelet filtering, widowing and clustering. 2.1. Data Collection 2. Experimental Methods To support a variety of experiments, we gathered streetlevel, urban canyon, carrier phase and position data at multiple locations in downtown Toronto (Canada). Four sites were selected to represent distinct levels of urban canyon effects ranging from moderate to extreme multipath interference. At Authorized licensed use limited to: Ryerson University Library. Downloaded on July 7, 2009 at 10:57 from IEEE Xplore. Restrictions apply.
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