By Peter Moo, Zhen Ding
Radar source administration (RRM) is key for optimizing the functionality of contemporary phased array radars, that are the first sensor for plane, ships, and land systems. Adaptive Radar source administration offers an advent to radar source administration (RRM), featuring a transparent evaluation of alternative techniques and methods, making it very appropriate for radar practitioners and researchers in and universities.
- 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 software Adapt_MFR
- Detailed descriptions and function effects for particular adaptive RRM techniques
- The merely publication totally devoted to adaptive RRM
- A complete remedy of phased array radars and RRM, together with activity prioritization, radar scheduling, and adaptive song replace rates
- Provides unique wisdom of particular RRM thoughts and their performance
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Extra resources for Adaptive Radar Resource Management
A more realistic rate-based approach was proposed by Tei-Wei , where real-time dwell scheduling was considered and significant performance improvement was achieved. This category of algorithms has some overlap with the NRL benchmark solutions discussed in the following section, as they both consider radar parameter optimization for better tracking performance. 5 Comments Adaptive update rate algorithms have been used in many radar systems. However, optimal adaptive rate is an ongoing topic.
106 This chapter presents two techniques for the adaptive scheduling of a multifunction radar (MFR). 1. 2, the two-slope benefit function scheduler (TSBFS) is presented. 1 Introduction An MFR typically has two sets of priorities: function priorities and task priorities. The function priorities are predetermined by the radar mission. For example, the following priority levels exist: 1. 2. 3. 4. 5. 6. 7. 8. high-priority tracks (highest priority); track maintenance; medium-priority tracks; plot confirmation; track initiation; low-priority tracks; surveillance and slow tracks; and receiver calibration and built-in-test (BIT) (lowest priority).
Time-balancing scheduling (TBS); and 3. adaptive update intervals for tracking. These techniques are described here in more detail. 2 shows the fuzzy logic decision tree and can be used to rank the relative importance of targets detected and tracked by the radar. 2 Decision tree for fuzzy logic adaptive target priority. decide when track accuracy for low priority targets may be relaxed when the radar is overloaded. The ability of the radar to selectively relax the detection and tracking requirements for lower-priority radar tasks, coupled with the need to adapt the task priority order for task scheduling, provides a tool to support the implementation of graceful degradation of radar performance in extreme overload.
Adaptive Radar Resource Management by Peter Moo, Zhen Ding