Institution
Defence Research and Development Laboratory
Facility•Hyderabad, India•
About: Defence Research and Development Laboratory is a facility organization based out in Hyderabad, India. It is known for research contribution in the topics: Turbulence & Mach number. The organization has 404 authors who have published 420 publications receiving 4183 citations. The organization is also known as: DRDL.
Papers published on a yearly basis
Papers
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01 Jan 2018
TL;DR: This study investigates use of genetic algorithms (GA) as an optimization procedure in the flight trajectory planner to be used in the real-time environment.
Abstract: Mission planning is a critical stage in launching a cruise missile against highly defended targets It is required to generate an optimal trajectory during combat scenario (real time) just before launch Typically, this type of engagement is carried by cruise missiles flying at low altitudes below 100 m In addition to air defense, terrain features also need to be avoided by following certain way-points This study investigates use of genetic algorithms (GA) as an optimization procedure in the flight trajectory planner to be used in the real-time environment
2 citations
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TL;DR: The proposed framework has been used to design the heater for one of the known published data and it is found that the predicted performance of RSH is in good agreement with the published data, establishing the accuracy of the developed framework.
2 citations
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18 Jan 1988TL;DR: This paper deals with the real time implementation of an image registration algorithm, for an application onboard a flight vehicle, where there are limitations on system power and space, in addition to the processing time constraint.
Abstract: This paper deals with the real time implementation of an image registration algorithm, for an application onboard a flight vehicle, where there are limitations on system power and space, in addition to the processing time constraint. Two images must be registered to find the similarity between them or to find the object motion in a scene. Real time in this application means an update time of 1/30th of a second i.e., at TV frame rate. The direct method using the normalised correlation function is chosen for implementation considering both the performance and the computational complexity. A hybrid approach using dedicated hardware for computation intensive part of the algorithm and a microprocessor based subsystem for other functions is adopted as a compromise between flexibility and efficiency. To meet the time constraint parallel pipelined architecture is used. To meet the low power requirement mostly CMOS devices are used. To meet the space constraint specific integrated circuits are being planned. A specific example of implementation is given.
2 citations
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01 Oct 2016
TL;DR: This paper presents a successful realization of distributed real-time Radar Simulation Test bed for testing mission critical systems and shows how distributed computing provides an elegant solution for its need of high computational resources.
Abstract: Testing of radar based systems is an arduous exercise and it is essential to develop a real-time radar simulator for testing such systems. However, as radar simulation test bed demands more computational resources to meet the real-time deadlines, it turns out to be more complicated than the system being tested. Distributed computing provides an elegant solution for its need of high computational resources. However, it calls for data, event and time synchronization among the processors. In this paper, we present a successful realization of distributed real-time Radar Simulation Test bed for testing mission critical systems.
2 citations
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TL;DR: The paper addresses and solves the guidance loop stability problem arising due to body rate coupling to the seeker, which becomes acute due to fast guidance time constant and higher subsystem BW required in order satisfying very stringent mission requirement.
2 citations
Authors
Showing all 406 results
Name | H-index | Papers | Citations |
---|---|---|---|
Debasish Ghose | 43 | 357 | 8172 |
Pawan Sinha | 40 | 181 | 7949 |
Surendra N. Tewari | 23 | 116 | 1621 |
Saggam Narendar | 23 | 51 | 1541 |
Sumana Srinivasan | 15 | 78 | 716 |
Debasis Chakraborty | 13 | 85 | 626 |
Doran Chakraborty | 9 | 24 | 277 |
S. Vathsal | 8 | 42 | 214 |
P. Manna | 7 | 15 | 201 |
P. Mastanaiah | 7 | 9 | 210 |
B.S. Sarma | 7 | 9 | 288 |
Malsur Dharavath | 7 | 13 | 157 |
Nirmit Prabhakar | 6 | 17 | 74 |
Niladri Mandal | 6 | 9 | 179 |
R.N Bhattacharjee | 5 | 6 | 51 |