• Geophysics and Geophysical Exploration
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• v.17 no.2
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• pp.88-94
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• 2014

Due to mechanical failure or geographical accessibility, the seismic data can be partially missed. In addition, it can be coarsely sampled such as crossline of the marine streamer data. This seismic data that irregular sampled and spatial aliased may cause problems during seismic data processing. Accurate and efficient interpolation method can solve this problem. Futhermore, interpolation can save the acquisition cost and time by reducing the number of shots and receivers. Among various interpolation methods, the Matching Pursuit method can be applied to any sampling type which is regular or irregular. However, in case of using sinusoidal basis function, this method has a limitation in spatial aliasing. Therefore, in this study, we have developed wavelet based Matching Pursuit method that uses wavelet instead of sinusoidal function for the improvement of dealiasing performance. In addition, we have improved interpolation speed by using inner product instead of L-2 norm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.6
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• pp.1094-1103
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• 2001

According to standard procedures as defined in the users handbook for sea level data processes, I was compared to Topex/Poseidon sea level data from the first 350days of mission and Tide Gauge sea level data from the Amsterdam- Crozet- Kerguelen region in the South Indian Ocean. The comparison improves significantly when many factors for the corrections were removed, then only the aliased oceanic tidal energy is removed by oceanic tide model(11) in this period. Making the corrections and smoothing the sea level data ()ver 60km along-track segments and the Tide Gauge sea level data for the time series results in the digital correlation and RMS difference between the two data of c=-0.12 and rms= 11.4cm, c=0.55 and rms=5.38cm, c=0.83 and rms=2.83cm, and c=0.24 and rms=6.72 for the Amsterdam, Crozet and Kerguelenplateau, and Kerguelen coast, respectively. It was also found that the Kerguelen plateau has a comparisons due to propagating signals(the baroclinic Rossby wave with velocity of -3.9 ~-4.2cm/sec, period of 167days and amplitude of 10cm) that introduce temporal lags(${\gamma}$: 10~30days) between the altimeter and tide gauge time series. The conclusion is that on timescales longer than about 10days the RMS sea level errors are less than or of the order of several centimeters and are mainly due to the effects of currents rather than the effects of stories(water temperature, density) and winds.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.385-390
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• 2006

This paper examines the sampling and jitter specifications and considerations for Global Navigation Satellite Systems (GNSS) software receivers. Software radio (SWR) technologies are being used in the implementation of communication receivers in general and GNSS receivers in particular. With the advent of new GPS signals, and a range of new Galileo and GLONASS signals soon becoming available, GNSS is an application where SWR and software-defined radio (SDR) are likely to have an impact. The sampling process is critical for SWR receivers, where it occurs as close to the antenna as possible. One way to achieve this is by BandPass Sampling (BPS), which is an undersampling technique that exploits aliasing to perform downconversion. BPS enables removal of the IF stage in the radio receiver. The sampling frequency is a very important factor since it influences both receiver performance and implementation efficiency. However, the design of BPS can result in degradation of Signal-to-Noise Ratio (SNR) due to the out-of-band noise being aliased. Important to the specification of both the ADC and its clocking Phase- Locked Loop (PLL) is jitter. Contributing to the system jitter are the aperture jitter of the sample-and-hold switch at the input of ADC and the sampling-clock jitter. Aperture jitter effects have usually been modeled as additive noise, based on a sinusoidal input signal, and limits the achievable Signal-to-Noise Ratio (SNR). Jitter in the sampled signal has several sources: phase noise in the Voltage-Controlled Oscillator (VCO) within the sampling PLL, jitter introduced by variations in the period of the frequency divider used in the sampling PLL and cross-talk from the lock line running parallel to signal lines. Jitter in the sampling process directly acts to degrade the noise floor and selectivity of receiver. Choosing an appropriate VCO for a SWR system is not as simple as finding one with right oscillator frequency. Similarly, it is important to specify the right jitter performance for the ADC. In this paper, the allowable sampling frequencies are calculated and analyzed for the multiple frequency BPS software radio GNSS receivers. The SNR degradation due to jitter in a BPSK system is calculated and required jitter standard deviation allowable for each GNSS band of interest is evaluated. Furthermore, in this paper we have investigated the sources of jitter and a basic jitter budget is calculated that could assist in the design of multiple frequency SWR GNSS receivers. We examine different ADCs and PLLs available in the market and compare known performance with the calculated budget. The results obtained are therefore directly applicable to SWR GNSS receiver design.