• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.12
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• pp.1275-1283
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• 2014

Characteristics of PCM(Pulse Code Modulation) waveform are suitable for target tracking. Especially in terms of dwell time, it is desirable to detect and track a moving target with the single PCM waveform for a MFR(Multi-Function Radar) which carries out multiple tasks. General PCM waveform processing includes Doppler filter bank caused by the characteristics of ambiguity function, to detect target and estimate Doppler frequency, which induces hardware burden and computational complexity. We propose a ML(Maximum Likelihood) based Doppler estimator for a PCM waveform, which is the closed form suboptimal solution and computationally efficient to estimate Doppler frequency and detect a moving target.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2339-2355
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• 2021

In this paper, a joint probabilistic data association algorithm based on loss function (LJPDA) is proposed so that the computation load and accuracy of the multi-target tracking algorithm can be guaranteed simultaneously. Firstly, data association is divided in to three cases based on the relationship among validation gates and the number of measurements in the overlapping area for validation gates. Also the contribution coefficient is employed for evaluating the contribution of a measurement to a target, and the loss function, which reflects the cost of the new proposed data association algorithm, is defined. Moreover, the equation set of optimal contribution coefficient is given by minimizing the loss function, and the optimal contribution coefficient can be attained by using the Newton-Raphson method. In this way, the weighted value of each target can be achieved, and the data association among measurements and tracks can be realized. Finally, we compare performances of LJPDA proposed and joint probabilistic data association (JPDA) algorithm via numerical simulations, and much attention is paid on real-time performance and estimation error. Theoretical analysis and experimental results reveal that the LJPDA algorithm proposed exhibits small estimation error and low computation complexity.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.789-790
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• 2008

In this paper, we introduce the multi-target-based auto surveillance algorithm. Multi-target-based surveillance system detects intrusion objects in the specified areas. The proposed algorithm can divide into two parts: i) background generation, ii) object extraction. In this paper, one of the optical flow equation methods for estimation of gradient method used to generate the background [2]. In addition, the objects and back- ground video images that are continually entering the differential extraction.

• Journal of Auto-vehicle Safety Association
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• v.3 no.2
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• pp.28-33
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• 2011

This paper presents driving path estimation algorithm for adaptive cruise control system and advanced emergency braking system using multi-sensor fusion. Through data collection, yaw rate filtering based road curvature and vision sensor road curvature characteristics are analyzed. Yaw rate filtering based road curvature and vision sensor road curvature are fused into the one curvature by weighting factor which are considering characteristics of each curvature data. The proposed driving path estimation algorithm has been investigated via simulation performed on a vehicle package Carsim and Matlab/Simulink. It has been shown via simulation that the proposed driving path estimation algorithm improves primary target detection rate.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.109-117
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• 2005

Range and velocity measurement algorithm is a procedure for estimating the accurate target position by using matched filter outputs equally spaced both in range and doppler frequency domain. Especially, in measurement algorithm for multi-function radar, it is necessary to consider processing time as well as accuracy in order to track multi-targets simultaneously. In this paper, we analyze range and velocity measurement algorithm using discriminator estimation method which is a technique applied to angle measurement of monopulse radar. The applied method required constant processing time for estimation can be used in multiple target tacking. But, it is necessary to consider measurement accuracy because of using minimum channel outputs for estimation. In the simulation, we show that the applied method is superior to the traditional gravity center measurement algorithm with respect to the accuracy performance and also analyze the characteristics of the proposed technique by calculating RMS error level as the processing parameters such as pulse width , channel step, etc. change.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.699-701
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• 1995

An input estimation technique is derived in multi-sensor environment. The proposed approach distribute the computational burden of input estimation to each local sensor and fusion center without loss of its optimality. The performances of proposed method in 2-sensor system are compared with those in single sensor system. Simulation results show that a reliable maneuvering target tracking system can be constructed in multi-sensor environment via proposed approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.253-260
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• 2012

Target detection is very difficult with complex clutters in IRST(Infrared Search and Track) system for a long distance target. Especially sea-clutter and ocean-surface with non-uniform temperature distribution make it difficult to detect incoming targets in images obtained in sea environment. In this paper, we propose a novel method based on morphological method for estimation of ocean surface with non-uniform temperature flow. In order to estimate the exact ocean surface temperature flow, we divided it into upper and lower bound flow. And after estimating it, the final ocean surface temperature flow is derived by a mean value of the estimated results. Also, we apply the multi-weighted technique with a variety of sizes of structure elements to overcome sub-sampling effect by using morphology method. Experimental results for ocean surface images acquired from many different environments are compared with results of existing method to verify the performance of the proposed methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.6
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• pp.545-556
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• 2016

JPDAF is a method of updating target's state estimation by using posterior probability that measurements are originated from existing target in multi-target tracking. In this paper, we propose a multi-target tracking algorithm for falling cluster bombs separated from a mother bomb based on JPDAS method which is obtained by applying fixed-interval smoothing technique to JPDAF. The performance of JPDAF and JPDAS multi-target tracking algorithm is compared by observing the average of the difference between targets' state estimations obtained from 100 independent executions of two algorithms and targets' true states. Based on this, results of simulations for a radar tracking problem that show proposed JPDAS has better tracking performance than JPDAF is presented.

• ETRI Journal
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• v.38 no.5
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• pp.1019-1029
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• 2016

The probability hypothesis density (PHD) filter is an effective means to track multiple targets in that it avoids explicit data associations between the measurements and targets. However, the target birth intensity as a prior is assumed to be known before tracking in a traditional target-tracking algorithm; otherwise, the performance of a conventional PHD filter will decline sharply. Aiming at this problem, a novel target birth intensity scheme and an improved measurement-driven scheme are incorporated into the PHD filter. The target birth intensity estimation scheme, composed of both PHD pre-filter technology and a target velocity extent method, is introduced to recursively estimate the target birth intensity by using the latest measurements at each time step. Second, based on the improved measurement-driven scheme, the measurement set at each time step is divided into the survival target measurement set, birth target measurement set, and clutter set, and meanwhile, the survival and birth target measurement sets are used to update the survival and birth targets, respectively. Lastly, a Gaussian mixture implementation of the PHD filter is presented under a linear Gaussian model assumption. The results of numerical experiments demonstrate that the proposed approach can achieve a better performance in tracking systems with an unknown newborn target intensity.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.12
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• pp.1045-1059
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• 2011

A 3-D multi-function radar(MFR) is a modern radar to provide various target information, such as range, doppler, and angle by performing surveillance, multiple target tracking, and missile guidance. In this paper, we introduced a real-time radar signal processor(RSP), which is a crucial component of MFR with its design, implementation using high-speed multiple DSP, and performance. Additionally, we verified that several advanced signal processing algorithms were well-performed in our RSP, such as MCA-CFAR algorithm for target detection in clutter environment, range and velocity measurement algorithm using discriminator estimation, and noise jammer detection algorithm using local minimum selection.