• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.2
• /
• pp.855-870
• /
• 2019

In this paper, an adaptive iterative algorithm is proposed for motion deblurring by using the salient intensity prior. Based on the observation that the salient intensity of the clear image is sparse, and the salient intensity of the blurred image is less sparse during the image blurring process. The salient intensity prior is proposed to enforce the sparsity of the distribution of the saliency in the latent image, which guides the blind deblurring in various scenarios. Furthermore, an adaptive iteration strategy is proposed to adjust the number of iterations by evaluating the performance of the latent image and the similarity of the estimated blur kernel. The negative influence of overabundant iterations in each scale is effectively restrained in this way. Experiments on publicly available image deblurring datasets demonstrate that the proposed algorithm achieves state-of-the-art deblurring results with small computational costs.

• Journal of Korea Multimedia Society
• /
• v.22 no.12
• /
• pp.1396-1403
• /
• 2019

The radar wind profiler data contaminates with various non-atmospheric components that produce errors in moments and wind velocity estimations. This study implemented an adaptive Gaussian model to detect and remove the clutter from the radar return. This model includes DC filtering, ground clutter recognition, Gaussian fitting, and cost function to mitigate the clutter component. The adaptive model tested for the various types of clutter components and found that it is effective in clutter removal process. It is also applied for the both time series and spectrum datasets. The moments estimated using this method are compared with those derived using conventional DC-filtering clutter removal method. The comparisons show that the proposed method effectively removes the clutter and produce reliable moments.

• Journal of Mechanical Science and Technology
• /
• v.19 no.9
• /
• pp.1742-1752
• /
• 2005

This paper presents a Multiple Target Tracking (MTT) Adaptive Cruise Control (ACC) system which consists of three parts; a multi-model-based multi-target state estimator, a primary vehicular target determination algorithm, and a single-target adaptive cruise control algorithm. Three motion models, which are validated using simulated and experimental data, are adopted to distinguish large lateral motions from longitudinally excited motions. The improvement in the state estimation performance when using three models is verified in target tracking simulations. However, the performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. The MTT-ACC system is tested under lane changing situations to examine how much the system performance is improved when multiple models are incorporated. Simulation results show system response that is more realistic and reflective of actual human driving behavior.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.15 no.6
• /
• pp.812-819
• /
• 2012

Interference and jamming are becoming increasing concern to a radar system nowdays. AESA(Active Electronically Steered Array) antennas and adaptive beamforming(ABF), in which antenna beam patterns can be modified to reject the interference, offer a potential solution to overcome the problems encountered. In this paper, we've developed a planar active phased array radar system, in which ABF, target detection and tracking algorithm operate in real-time. For the high output power and the low noise figure of the antenna, we've designed the S-band TRMs based on GaN HEMT. For real-time processing, we've used wavelenth division multiplexing technique on fiber optic communication which enables rapid data communication between the antenna and the signal processor. Also, we've implemented the HW and SW architecture of Real-time Signal Processor(RSP) for adaptive beamforming that uses SMI(Sample Matrix Inversion) technique based on MVDR(Minimum Variance Distortionless Response). The performance of this radar system has been verified by near-field and far-field tests.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.12
• /
• pp.2417-2424
• /
• 2016

Small size and light weight is very important for components used in radar mounted platform such as airborne radar. Recently, the active phased array radar is developed as an array of antennas for thousands of transmit/receive modules to be used as a multi-function radar that can detect and track targets. In this case, the size and weight of the transmit/receive modules are critical factor for developing the radar. In this paper, we developed a compact transmit/receive module using the 10W RF MEMS switch domestically localizing and reduced the circuit area to about 86.5% compared to using a circulator. The developed module satisfies not only electrical requirements but also MIL-STD's environmental specifications. So it can be used in a military device. It can be used at adaptive tunable receivers, reconfigurable smart active antennas and wide band beam electrical steering antennas.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.21 no.1
• /
• pp.23-29
• /
• 2013

This paper presents a tracking filter of radar beacon system (RBS) for automatic takeoff and landing of an unmanned aerial vehicle. The proposed tracking filter is designed as the decoupled tracking filter to reduce the computational burden. Also, an adaptive estimation method of the measurement error covariance is proposed to provide an improved tracking performance compared to the conventional decoupled tracking filter whenever the accuracy of RBS observations is degraded. 100 times Monte Carlo runs performed to analyze the performance of the proposed tracking filter in case of normal operation and degraded operations, respectively. The simulation results show that the proposed tracking filter provides the improved tracking accuracy in comparison with the conventional decoupled tracking filter.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.26 no.6
• /
• pp.140-146
• /
• 1989

In many situations, radar targets are embedded in a clutter environment and clutter rejection is required. The clutter is unwanted radar echoes and may arise owing to reflections from ground and weather disturbances and statistical properties of the clutter vary with range and azimuth as well as time. That is, adaptive signal processing is required. In this paper, a clutter suppression algorithm based on the clutter whitening filter (WF) and doppler filter bank(DFB) is described which provides improved performance compared with conventional nonadaptive clutter suppression algorithm that is the cascaded moving target indicator (MTI) and (DFB). The clutter whitening filter algorithm is based on the Burg's maximum entropy method.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.506-509
• /
• 2005

An adaptive ${\alpha}-{\beta}$ tracker is proposed for tracking maneuvering targets with a track-while-scan radar system. The tracker gain is updated on-line corresponding to the adjusted process noise variance which is obtained via time averaging of the process over a sliding window. The adjusted process noise variance is used to compute the maneuverability index for the tracker gain based on the steady-state Kalman filter equation for each epoch. It is shown via simulation that the proposed approach provides robust and accurate position estimates during the target maneuver while the performance of the conventional ${\alpha}-{\beta}$ tracker is shown much degraded.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.5 s.305
• /
• pp.157-164
• /
• 2005

The conventional adaptive detectors can not maintain sufficient detection performance at the presence of non-stationary clutter with unknown characteristics. This is caused by the lack of a priori information about clutter parameters changing over radar coordinates. To solve this problem, it is necessary to use clutter classifiers which have functions, such as the selection of the applied algorithm and its parameters extraction according to clutter conditions. In this paper, we describe the implementation of a clutter environment classifier for adaptive processing. In the environment classifier implemented on Visual C++, the extraction of the parameters and selection of processing algorithm for the adaptive processing unit are possible, and the result of algorithms can be verified at each stage.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.2
• /
• pp.868-874
• /
• 2018

In this paper, we propose a new jammer suppression algorithm that uses orthogonal waveform space projection (OWSP) processing for a multiple input multiple output (MIMO) radar system exposed to a jamming signal. Generally, a conventional suppression algorithm based on adaptive beamforming (ABF) needs a covariance matrix composed of the jammer and noise only. By exploiting the orthogonality of the transmitting waveforms of MIMO, we can construct a transmitting waveform space (TWS). Then, using the OWSP processing, we can build a space orthogonal to the TWS that contains no SOI. By excluding the SOI from the received signal, even in the case that contains the SOI and jamming signal, the proposed algorithm makes it possible to evaluate the covariance matrix for ABF. We applied the proposed OWSP processing to suppressing the jamming signal in bistatic MIMO radar. We verified the performance of the proposed algorithm by comparing the SINR loss to that of the ideal covariance matrix composed of the jammer and noise only. We also derived the computational complexity of the proposed algorithm and compared the estimation of the DOD and DOA using the SOI with those using the generalized likelihood ratio test (GLRT) algorithm.