An Algorithm for Target Detection, Identification, Tracking and Estimation of Motion for Passive Homing Missile Autopilot Guidance

Sharma, Manvinder; Gupta, Anuj

doi:10.1007/978-981-15-7130-5_5

Cited by 13 publications

(4 citation statements)

References 15 publications

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“…Due to tunneling current through gate oxide insulator, gate oxide leakage power is another contributor to leakage power. [14] For nano scale gate oxide leakage is comparable to subthreshold leakage power [15][16][17]. For reducing this oxide leakage current high k dielctric materials can be used.…”

Section: Figure 1 Subthreshold Leakage Of Nmosmentioning

confidence: 99%

Implementation and Modeling of Low Power Sleepy Stack Sram

Kakkar¹

2022

joas

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For the future technologies in which the devices and circuits are integrating more, low power consuming devices are needed. Mostly the reduction of power dissipation work is concentrated on switching and leakage current. However, sub threshold current is also a big factor which leads to power consumption especially for memories. In this paper, leakage power of SRAM memory cell is reduced by power gated sleepy stack structure which leads to lesser power dissipation. The power dissipation is reduced to 226 µW with proposed technique compared with power dissipation of conventional 6T SRAM cell which had 740 µW. With lesser power dissipation the circuit can have more battery backup and lesser heat emission

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Section: Figure 1 Subthreshold Leakage Of Nmosmentioning

confidence: 99%

Implementation and Modeling of Low Power Sleepy Stack Sram

Kakkar¹

2022

joas

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“…In recent years, with the vigorous development of electronic information technology and modern control technology [1], target ltering and tracking technology has been widely used in automatic driving [2], smart security [3], tra c planning [4], navigation, and positioning [5] and has played a vital role. Its essence is to use the state information of the target at the current moment and the measurement information obtained by the sensor to realize the method of estimating the state information at the next moment [6].…”

Section: Introductionmentioning

confidence: 99%

Target Filter Tracking Algorithm Based on IABBSCA-IMM

Jiao

et al. 2022

Mathematical Problems in Engineering

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Aiming at the problem that the probability transition matrix is set by prior information and the filtering parameters are fixed in the traditional interactive multimodel (IMM) algorithm, which leads to the model probability lag in the switching process and the low filtering and tracking accuracy, an interactive multimodel filter tracking (IABBSCA-IMM) algorithm with improved parameter adaptive and bare bone sine cosine optimization is proposed. First, the Markov probability transition matrix is dynamically adjusted and limited conditions are added through the parameter adaptation method; then, the filtering parameters Q and R are optimized by the bare bones sine cosine algorithm (BBSCA); finally, three motion models of CV (uniform velocity motion), CA (uniform acceleration motion), and CT (uniform velocity turning motion) are used to conduct filtering and tracking experiments on the target. The simulation results show that, compared with the IMM algorithm, the AMP-IMM algorithm, the IASCA-IMM algorithm, and the IABBSCA-IMM algorithm proposed in this study have the smallest position and velocity root mean square error (RMSE) in the X and Y directions, and the accuracy is better.

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“…Outlier detection is a field of data mining with a wide range of applications in several domains varying from intrusion detection (Angelo et al, 2018), process monitoring (Wang and Mao, 2019), detection of fake iris images (2018), security threats (Sharma and Gupta, 2021) and identification of credit card frauds (Carcillo et al, 2019). Outlier points might be of several types that may occur in different magnitude, intensity and frequency.…”

Section: Introductionmentioning

confidence: 99%

Simulated Workbench Design for Characterisation and Selection of Appropriate Outlier Ensemble Algorithm

Divya

Bhasi

Kumar

2022

International Journal of Information System Modeling and Design

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Outlier ensembles can enhance the performance of outlier detection algorithms. However, identification of an appropriate outlier ensemble algorithm for the given application is a difficult task. In order to achieve this function, the performance features of outlier ensembles with gathered data types containing a certain set of outliers have been characterised and their ensemble performance analysed in this paper. The proposed methodology suggests comparing data and anomalous features of a given real time application to the data set available in the proposed workbench. Users can use the results of experiments conducted using the workbench to identify highly efficient algorithms for their application without undertaking further analysis once matching data is located in the workbench. Therefore, this research paper act as a recommendation system that enables data scientists from various fields to pick an effective outlier ensemble for their application.

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An Algorithm for Target Detection, Identification, Tracking and Estimation of Motion for Passive Homing Missile Autopilot Guidance

Cited by 13 publications

References 15 publications

Implementation and Modeling of Low Power Sleepy Stack Sram

Implementation and Modeling of Low Power Sleepy Stack Sram

Target Filter Tracking Algorithm Based on IABBSCA-IMM

Simulated Workbench Design for Characterisation and Selection of Appropriate Outlier Ensemble Algorithm

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