Peter Moo, Zhen Ding's Adaptive Radar Resource Management PDF

By Peter Moo, Zhen Ding

ISBN-10: 0128029021

ISBN-13: 9780128029022

ISBN-10: 0128042109

ISBN-13: 9780128042106

Radar source administration (RRM) is essential for optimizing the functionality of recent phased array radars, that are the first sensor for airplane, ships, and land structures. Adaptive Radar source administration provides an creation to radar source administration (RRM), proposing a transparent evaluation of other ways and methods, making it very appropriate for radar practitioners and researchers in and universities.

Coverage comprises:

  • RRM’s position in optimizing the functionality of recent phased array radars
  • The benefits of adaptivity in imposing RRM
  • The function that modelling and simulation performs in comparing RRM performance
  • Description of the simulation software Adapt_MFR
  • Detailed descriptions and function effects for particular adaptive RRM techniques
  • The basically ebook absolutely devoted to adaptive RRM
  • A finished remedy of phased array radars and RRM, together with activity prioritization, radar scheduling, and adaptive music replace rates
  • Provides special wisdom of particular RRM options and their performance

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Additional resources for Adaptive Radar Resource Management

Example text

Scenario 1 has a total of 52 targets, where each target is present in the scenario for some portion of the scenario timeline. Because all targets are not necessarily present at any given time, the total number of targets in the simulation may be fewer than 52 at any given time. The targets may be surface or airborne platforms. Each target is specified by a unique platform identification, location, velocity, trajectory, and RCS. Scenario 2 has a total of 152 targets. These targets include the 52 targets from Scenario 1, 50 targets which are replicated from the original 52 targets, and 50 bird targets.

10 shows track completeness as a function of target index. Adaptive and Nonadaptive RRM have similar track completeness values for most targets, with some minor exceptions. 11 presents track occupancy as a function of time. 11 shows that Adaptive RRM has significantly lower track occupancy than Nonadaptive RRM, while achieving similar values of track completeness. The use of Adaptive RRM allows the radar to allocate less time to tracking while maintaining the same track completeness as Nonadaptive RRM.

Therefore, the adaptive update rate algorithms are resource-aided algorithms. Twenty-three papers are collected in this category [70–92]. 2 A Foundation for Adaptive Update Rate Tracking Daum and Fitzgerald [70] investigated the use of covariance coordinates of various kinds for decoupling Kalman trackers, which resulted in three benefits: 1. reduced computational cost; 2. alleviation of ill-conditioning; and 3. mitigation of nonlinear effects. 30 Adaptive Radar Resource Management This paper provides a foundation for phased array radar tracking where the update rate is variable, and the ill-conditioning and nonlinear issues are more serious.

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Adaptive Radar Resource Management by Peter Moo, Zhen Ding

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