• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.388-390
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• 2006

This paper presents a hybrid SoC design for phase detection of single tone signal. The designed hybrid SoC is composed of three functional blocks, i.e., an analog to digital converter module, a phase detection module and a controller module. A design of the controller module is based on a 16-bit RISC architecture. An I/O interface and an LCD control interface for transmission and display of phase measurement values are included in the design of the controller module. A design of the phase detector is based on a recursive sliding-DFT. The recursive architecture effectively reduces the gate numbers required in the implementation of the module. The ADC module includes a single-bit second-order sigma-delta modulator and a digital decimation filter. The decimation filter is designed to give 98dB of SNR for the ADC. The effective resolution of the ADC is enhanced to 98dB of SNR by the incorporation of a pre FIR filter, a 2-stage cascaded integrator- comb(CIC) filter and a 30-tab FIR filter in the decimation. The hybrid SoC is verified in FPGA and implemented in 0.35 CMOS Technology.

• Journal of KIEE
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• v.11 no.1
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• pp.21-26
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• 2001

This paper considers the problem of robust H$\infty$ filter is derived by using the equivalence relationship between the FIR filter and the recursive filter, that would be guarantee a prescribed H$\infty$ performance in the continuous-time context, irrespective of the parameter uncertainty and unknown initial states.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.12
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• pp.1079-1085
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• 2013

Due to the limited power supply resources, it is essential that the minimization of algorithmic operation and the reduction of the hardware logical-resources in the design of the satellite transponder. It is also required that the transponder process the signals of various bandwidth efficiently, that is suitble for the SDR-based implementation. This paper proposes a variable rate down sampler which can provide variable bandwidth and data rate for carrier, ranging and sub-band command signals respectively. The proposed down sampler can provide multiple $2^M$ decimated outputs from a single half band filter with recursive arithmetic architecture, which can minimize the hardware resources as well as the arithmetic operations. The algorithm for hardware implementation as well as the analysis for the passband flatness and aliasing is presented and varified by the FPGA implementation.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.779-788
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• 2017

System identification and damage detection for structural health monitoring have received considerable attention. Various time domain analysis methodologies based on measured vibration data of structures have been proposed. Among them, recursive least-squares estimation of structural parameters which is also known as parametric Kalman filter (PKF) approach has been studied. However, the conventional PKF requires that all the external excitations (inputs) be available. On the other hand, structural uncertainties are inevitable for civil infrastructures, it is necessary to develop approaches for probabilistic damage detection of structures. In this paper, a parametric Kalman filter with unknown inputs (PKF-UI) is proposed for the simultaneous identification of structural parameters and the unmeasured external inputs. Analytical recursive formulations of the proposed PKF-UI are derived based on the conventional PKF. Two scenarios of linear observation equations and nonlinear observation equations are discussed, respectively. Such a straightforward derivation of PKF-UI is not available in the literature. Then, the proposed PKF-UI is utilized for probabilistic damage detection of structures by considering the uncertainties of structural parameters. Structural damage index and the damage probability are derived from the statistical values of the identified structural parameters of intact and damaged structure. Some numerical examples are used to validate the proposed method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.3
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• pp.317-325
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• 2016

This paper describes the technique for Radar Particle filter for TBD(Track Before Detect) processing. TBD technique is applied when target is difficult to detect due to low signal-to-noise ratio caused by strong clutter environments, small RCS targets and stealth targets. Particle filter is suitable for a recursive TBD algorithm and has improved estimation accuracy than Kalman filter. In this paper, we will present a new method of calculating particle weight, when observation values(including strong clutter) are received at the same time. Estimation error performance of the particle filter algorithm is analyzed by using the virtual radar observation scenario.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.3
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• pp.21-26
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• 2010

This paper deals with the precise parameter estimation of an air vehicle without a priori information. First, Recursive Least Squares technique, which is an equation error method and does not require any a priori information, is applied and then the extended Kalman filter is used to tune parameters more precisely. To show the performance, a nonlinear longitudinal missile model is simulated and the parameters are estimated. The results show that this consecutive application of the techniques gives a very good estimation performance.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.2
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• pp.113-120
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• 1999

One of the important challenges facing control engineers in developing automated machineryis to be able to monitor the machines using remote sensors. Observrs are often used to reconstruct the machine variables of interest. However, conventional observers are unalbe to observe the machine variables when the machine models, upon which the observers are based, have inputs that cannot be measured. Since this is often the case, the authors previsously developed a steady-state optimal state and input observer for time-invariant systems [1], this paper extends that work to time-variant systems. A recursive observer, similar to a Kalman-Bucy filter, is developed . This optimal observer minimizes the trace of the error variance for discrete , linear , time-variant, stochastic systems with unknown inputs.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.305-307
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• 1992

This paper presents a technique, which identifies both process noise covariance and sensor noise covariance by using innovation correlation test. A correlation test, which checks whether the square root Kalman filter is workingly optimal or not, is given. The system is stochastic autoregressive moving-average model with auxiliary white noise Input. The linear quadratic Gaussian control is used for minimizing stochastic cost function. This paper indentifies Q, R, and estimates parametric matrics $A(q^{-1}),B(q^{-1}),C(q^{-1})$ by means of extended recursive least squares and model reference control. And The proposed technique has been validated in simulation results on the fourth order system.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.759-764
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• 1998

We propose a novel algorithm capable of recognizing the road lane by image processing. Considering the fact that the direction and location of road lane are maintained similarly in successive images we formulate a function to represent the property. However, as noises play the role of making a lot of similar patterns appear and disappear in the road image, keeping of robustness in the lane detection has been known a difficult work. To overcome this problem, we introduce the following three ideas: 1) design of a function based on an edge direction and magnitude, 2) construction of a recursive filter to estimate the function recursively for successive images, 3) principal axis-based line fitting. These concepts enhance the adaptability to cope with the random environment of traffic scene and eventually lead to the reliable detection of a road lane.

• Journal of the korean society of oceanography
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• v.35 no.4
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• pp.192-199
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• 2000

Standard CTD data processing recommended by Sea-Bird Electronics produced thermal-lag corrections larger than 0.1 psu for the data taken during the CREAMS expeditions in the northern part of the East/Japan Sea where a vertical temperature gradient frequently exceeds 1.0$^{\circ}$C/m in the upper 100 m near the sea surface. As the standard processing is based upon a recursive filter which was introduced by Lueck and Pickle (1990), coefficients of the recursive filter have been newly derived for the CREAMS data by minimizing the difference between salinities of downcast and upcast in temperature-salinity domain. The new coefficients are validated by comparison with salinities measured by a salinometer, AUTOSAL 8400B. An accurate correction for the thermal-lag is critical in identifying water masses at intermediate depth in the East/japan Sea.