• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2033-2036
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• 2004

A novel approach to estimate the real time moving trajectory of an object is proposed in this paper. The object position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Kalman filter and neural networks are utilized. Since the Kalman filter needs to approximate a non-linear system into a linear model to estimate the states, there always exist errors as well as uncertainties again. To resolve this problem, the neural networks are adopted in this approach, which have high adaptability with the memory of the input-output relationship. Kohonen Network(Self-Organized Map) is selected to learn the motion trajectory since it is spatially oriented. The superiority of the proposed algorithm is demonstrated through the real experiments.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.565-568
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• 2001

이 논문에서는 미디언 필터의 선형 조합을 통해 임의의 주파수 특성을 갖는 필터 구조와 그 설계 방법을 제안한다. Linear-phase FIR 저대역통과 필터의 홀수번째 필터 계수의 부호를 바꾸면 FIR 고대역 통과 필터를 얻을 수 있는데, 이것은 필터 계수의 부호가 모두 양수인 두 개의 부분 필터의 차와 같은 모양을 가진다. 이 과정을 일반화하여 비선형 필터에 적용하면 LCWM(linear combination of median filter)필터는 가중 미디언 부필터(sub-filter)의 선형 조합으로 구성된다. 이는 선형 대수학에서 어떤 공간상의 임의의 벡터가 그 공간의 기저 (basls) 벡터들의 선형 조합으로 표현된다는 사실과 유사하다. 따라서 부필터의 필터 계수를 기저 벡터로이용하여 얻어지는 기저 행렬과 필터의 주파수 특성을 조절하는 계수 벡터를 구함으로써 LCWM 필터를 설계할 수 있다. 제안된 필터 설계 방법을 이용하면 특정 주파수 특성을 가지는 FIR 필터와 유사한 특성을 갖는 비선형 필터 구조를 만들 수 있다. LCWM 필터는 고대역 통과, 저대역 통과, BP(band-pass), BS(band-stop)의 임의의 주파수 특성을 가지는 필터로 설계될 수 있음이 실험을 통해 확인되었다.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.129-132
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• 1999

This paper deals with the optimal filtering problem constrained to input noise signal corrupting the measurement output for linear discrete-time systems. The transfer matrix H$_2$and/or H$_{\infty}$ norms are used as criteria in an estimation error sense. In this paper, the mixed $H_2/H_{\infty}$ filtering Problem in lineal discrete-time systems is solved using the LMI approach, yielding a compromise between the H$_2$and H$_{\infty}$ filter designs. This filter design problems we formulated in a convex optimization framework using linear matrix inequalities. A numerical example is presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.627-633
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• 2000

In this paper, the polyphase filter which has micro ripple characteristic in the passband is proposed. This filter consists of the digital all-pass filter of parallel structure and it is the half-band filter with all zeros in unit circle. To approach easily in designing hardware, we determined the coefficients to the 16bit 1.15 format. To evaluate the performance of this filter, we analyzed the phase characteristic in each branch and each filter with small coefficients. Also, we simulated the phase characteristic of passband and stopband, group delay. As the result, we obtained the micro ripple characteristic and linear phase in the passband.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.357-357
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• 2000

In this study, we consider a multi-input multi-output styrene polymerization reactor system for which the monomer conversion and the weight average molecular weight are controlled by manipulating the jacket inlet temperature and the feed flow rate. The reactor system is identified by using a linear subspace identification method and then the output feedback model predictive controller is constructed on the basis of the identified model. Here we use the Best Linear Unbiased Estimation (BLUE) filter as a stochastic estimator instead of the Kalman filter. The BLUE filter observes the state successfully without any a priori information of initial states. In contrast to the Kalman filter, the BLUE filter eliminates the offset by observing the state of the augmented system regardless of a priori information of the initial state for an integral white noise augmented system. A BLUE filter has a finite impulse response (FIR) structure which utilizes finite measurements and inputs on the most recent time interval [i-N, i] in order to avoid long processing times.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5A
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• pp.618-633
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• 2000

In this paper, a Gaussian interpolation filter and cubic interpolation filter are presented to do more accurate channel estimation compared to the conventional linear interpolation filter for COFDM systems. In addition to an interpolation filter, a low pass filter using FFT and IFFT is also presented to reduce the noisy components of a channel estimate obtained by an interpolation filter. Channel estimates after low-pass filtering combined with interpolation filters can lower the error floor compared to the use of only interpolation filters. Computer simulation demonstrates that the presented channel estimation methods exhibit an improved performance compared to the conventional linear interpolation filter for COFDM systems in time-varying multipath fading channel and0.1 ~ 0.2 dB of Eb/No difference at BER=10-4 when the perfect channel estimation is compared.

• Journal of Advanced Navigation Technology
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• v.20 no.1
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• pp.53-58
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• 2016

In this paper, we propose a novel quadratic Kalman filter based object tracking algorithm using moving pictures. Quadratic Kalman filter, which is introduced recently, has not yet been applied to the problem of 3-dimensional (3-D) object tracking. Since the mapping of a position in 2-D moving pictures into a 3-D world involves non-linear transformation, appropriate algorithm must be chosen for object tracking. In this situation, the quadratic Kalman filter can achieve better accuracy than extended Kalman filter. Under the same conditions, we compare extended Kalman filter, unscented Kalman filter and sequential importance resampling particle filter together with the proposed scheme. In conculsion, the proposed scheme decreases the divergence rate by half compared with the scheme based on extended Kalman filter and improves the accuracy by about 1% in comparison with the one based on unscented Kalman filter.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.134-143
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• 1999

In this paper, in order to implement the IDWT(inverse discrete wavelet transform) with relatively low complexity, we propose a VLSI architecture for odd-tap linear-phase IDWT filters. By considering the symmetric property of the linear phase filter, the input is added to the one located at symmetrical position of the filter before filtering. Then. we rearrange the delay line of the filter in a U-shaped fashion. requiring no global interconnection between the components. The proposed architecture for the IDWT filter consists of delay units. operator units, adder units. and postprocessor unit. Since each units are configured regularly and interconnected locally. the proposed architecture can accommodate arbitrary linear phase IDWTs by simply adding/removing the corresponding units. The M -level IDWT can be implemented by interconnecting the proposed architecture in a cascaded or semi-recursive form. It is expected that the proposed architecture for the IDWT can be effectively employed in the related area including MPEG-4, since the proposed architecture is less complex than the conventional architectures.

• Economic and Environmental Geology
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• v.18 no.1
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• pp.41-47
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• 1985

The filtering ability of $J_0$ and $J_1$ digital linear filters is compared by means of an adaptive linear filter. Any $J_0$ domain Hankel transform integral can be transformed mathematically into its corresponding $J_1$ domain integral. The apparent resistivities for any electrode configuration employed in resistivity soundings can be evaluated with a single $J_1$ filter. The $J_1$ filter usually has similar accuracy to, but shorter length than, the corresponding $J_0$ filter. The domain transformation from $J_0$ to $J_1$ enables us to use effective expressions of apparent resistivity, involving $J_1$ alone, not only for Schlumberger but also for dipole-dipole array.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1679-1683
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• 1997

In this paper a linear Kalman filter for calibration of gimballed inertial navigation system(GINS) is designed and its performace is analyzed through the simulation with a real navigation data. Simulation results show that the proposed Kalman filter gives a good performance to calibrate the sensor errors.