• Journal of Korea Multimedia Society
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• v.8 no.8
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• pp.1051-1056
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• 2005

Least mean square(LMS) algorithm is one of the most popular algorithm in adaptive signal processing because of the simplicity and the small computation. But the convergence speed of time domain adaptive algorithm is slow when the spread width of eigen values is wide. Moreover we have to choose the step size well for convergency in this paper, we use adaptive algorithm of wavelet transform. And we propose a new wavelet based adaptive algorithm of wavelet transform. And we propose a new wavelet based adaptive algorithm with variable step size, which Is linear to absolute value of error signal. We applied this algorithm to adaptive noise canceler. Simulation results are presented to compare the performance of the proposed algorithm with the usual algorithms.

• ETRI Journal
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• v.41 no.3
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• pp.316-325
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• 2019

Accurate suppressive jamming is a prominent problem faced by radar equipment. It is difficult to solve signal detection problems for extremely low signal to noise ratios using traditional signal processing methods. In this study, a joint sensing dictionary based compressed sensing and adaptive iterative optimization algorithm is proposed to counter suppressive jamming in information domain. Prior information of the linear frequency modulation (LFM) and suppressive jamming signals are fully used by constructing a joint sensing dictionary. The jamming sensing dictionary is further adaptively optimized to perfectly match actual jamming signals. Finally, through the precise reconstruction of the jamming signal, high detection precision of the original LFM signal is realized. The construction of sensing dictionary adopts the Pei type fast fractional Fourier decomposition method, which serves as an efficient basis for the LFM signal. The proposed adaptive iterative optimization algorithm can solve grid mismatch problems brought on by undetermined signals and quickly achieve higher detection precision. The simulation results clearly show the effectiveness of the method.

• Journal of Korea Multimedia Society
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• v.8 no.1
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• pp.46-55
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• 2005

In this paper, we realize the panoramic infrared warning system to detect the small threaten object and propose the infrared image enhancement method to improve the warning ability of this system. This system composes of the sense head unit, the signal processing unit, and so on. In the proposed system, the sense head unit acquires the panoramic IR image with 360 degree field of view(FOV) by rotating the thermal sensor. The signal processing unit divides panoramic image into four sub-images with 90 degree FOV and computes the adaptive plateau value by using statistical characteristics of each subimage. Then the histogram equalization is performed for each subimage by using the adaptive plateau value. We realize the signal Processing unit by using the DSP and FPGA to perform the proposed method in real time. Experimental results show that the proposed method has better discrimination and lower false alarm rate than the conventional methods in this warning system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.7
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• pp.500-507
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• 2018

A three-channel radio frequency (RF) monopulse receiver using a data signal with a maximum transmission rate of 274 Mbps was designed. A monopulse receiver using a broadband communication signal was designed to operate in the Ku band, and it consists of a down-conversion module and a signal-processing module. To satisfy the performance of the proposed RF monopulse receiver, a signal-processing function less than the reception sensitivity for each transmission rate according to the adaptive transmission rate is required. To minimize signal reception and mutual frequency interference of various bandwidths, two RF filters were applied. To verify the satisfaction of system requirements, an AWR Corp. simulation tool was used.

• Journal of the Korea Society of Computer and Information
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• v.1 no.1
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• pp.53-64
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• 1996

The methods for designing the adaptive filter performing DSP(digital signal processing)functions In mobile communication systems are Least-squares algorithm. Fast-Kalman and adaptive lattice algorithm. Least-squares algorithm It fast convergence algorithm for signal Processor of adaptive equallizer and used for eliminating inter symbol Interference which occur inmultiple path fading channel In mobille communication systems. In this paper. we propose the method of control adjustably algebra characteristics of signal vector that is sampling at some of new data sequence and confirm the improvement of fast convergence and iterative performance speed compared to existing algorithms by computer simulation.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.128-132
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• 2011

Least mean square adaptive algorithms have played important role in radar, sonar, speech processing, and mobile communication. In mobile communication area, the convergence rate of a LMS algorithm is quite important. However, LMS algorithms have slow and non-uniform convergence rate problem For overcoming these shortcomings, various variable step LMS adaptive algorithms have been studied in recent years. Most of these recent LMS algorithms have used complex variable step methods to get a rapid convergence. But complex variable step methods need a high computational complexity. Therefore, the main merits such as the simplicity and the robustness in a LMS algorithm can be eroded. The proposed deterministic variable step LMS algorithm is based upon a simple deterministic function for the step update so that the simplicity of the proposed algorithm is obtained and the fast convergence is still maintainable.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8C
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• pp.745-757
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• 2007

In this paper, we propose a design of GPS anti-jamming system and its operational method, which can effectively suppress interference and jamming signals induced in GPS receiver. The 7-array antenna used in the proposed system is composed of conventional 6 equi-spaced circular elements with one element on the center of antenna and can be efficiently operated under power-constrained conditions. Futhermore, in this paper, we analyze the structure and complexity of STAP and SFAP which are well known techniques in adaptive array antenna signal processing, and we compare the BER performances between STAP and SFAP in various jamming environment based on the same complexity.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.3
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• pp.157-162
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• 2005

This paper presents an adaptive compensator using the fuzzy systems for robot manipulator with unknown frictions. In general, frictions are neglected or dynamic frictions are only considered in robot control theories. The proposed control method considers viscous frictions as well as dynamic frictions. Using the property that the frictions of joints are decoupled, SISO-fuzzy systems are utilized to approximate each friction. The stability of overall control system is proven and the adaptive laws are derived based on Lyapunov stability theorey. To verify the validity of the proposed control strategy, the results of computer simulations are shown for 2-link robot manipulator. The ability of approximating of the fuzzy system is also shown.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1C
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• pp.1-8
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• 2007

LMS(Least Mean Square) algorithm using steepest descent way in adaptive signal processing requires simple equation and is used widely because of the less complexity. But eigenvalues change by width of input signals in time domain, so the rate of convergence becomes low. In this paper, we propose a new fast running FIR filter structure that improves the convergence speed of adaptive signal processing and the same performance as the existing fast wavelet transform algorithm with less computational complexity. The proposed filter structure is applied to wavelet based adaptive algorithm. Simulation results show a better performance than the existing one.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.85-90
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• 2004

This paper proposes the wavelet image coding using the significant cluster extraction by morphology and the adaptive quantization. In the conventional MRWD method, the additional seed data takes large potion of the total data bits. The proposed method extracts the significant cluster using morphology to improve the coding efficiency. In addition, the adaptive quantization is proposed to reduce the number of redundant comparative operations which are indispensably occurred in the MRWD quantization. The experimental result shows that the proposed algorithm has the improved coding efficiency and computational cost while preserving superior PSNR