Adaptive Radar Resource Management by Peter Moo, Zhen Ding

By Peter Moo, Zhen Ding

Radar source administration (RRM) is essential for optimizing the functionality of contemporary phased array radars, that are the first sensor for plane, ships, and land systems. Adaptive Radar source administration supplies an creation to radar source administration (RRM), featuring a transparent review of alternative techniques and strategies, making it very appropriate for radar practitioners and researchers in and universities.

Coverage comprises:

  • RRM’s position in optimizing the functionality of contemporary phased array radars
  • The merits of adaptivity in imposing RRM
  • The function that modelling and simulation performs in comparing RRM performance
  • Description of the simulation device Adapt_MFR
  • Detailed descriptions and function effects for particular adaptive RRM techniques
  • The purely e-book absolutely devoted to adaptive RRM
  • A complete therapy of phased array radars and RRM, together with job prioritization, radar scheduling, and adaptive music replace rates
  • Provides distinct wisdom of particular RRM recommendations and their performance

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Additional info for Adaptive Radar Resource Management

Sample text

2 Equal Priority Looks .................................................... 3 Looks with Unequal Priorities ........................................ 4 Sub-Scheduler Operation .............................................. 4 Scheduling Examples ................................................... 1 Examples 3A and 3B: Tracking Looks in Condition II ....... 2 Examples 4A and 4B: Tracking Looks in Condition III ...... 97 Adaptive Radar Resource Management. 00004-1 Copyright © 2015 Crown Copyright Published by Inc.

A constraint of 4% is to be imposed on the number of lost tracks. When FAs and ECM are present in an actual radar system, algorithms for reacquiring the target and coasting the target tracks through jamming signals are required in order to maintain a track. Since the benchmark problems were proposed, many solutions, such as the IMM-Multiple Hypothesis Tracker (MHT), alpha-beta tracker, the IMM estimator with probabilistic data association filter (IMMPDAF), adaptive IMM and CSO tracker, have been proposed [100–102, 108, 110].

The priority value, as calculated by the fuzzy logic prioritization technique, dynamically varies with the characteristics and dynamics of a target. As a result, the number of high-, medium-, and low-priority targets also varies throughout the simulation. 9b shows the total number of targets, including the number of high-, medium-, and low-priority 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.

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