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Self-adaptive-termination MIMO (Multi-Input Multi-Output) radar optimization netting method in multi-surveillance area

A monitoring area and self-adaptive technology, applied in data processing applications, instruments, computing models, etc., to reduce the waste of time and computing resources and improve monitoring performance

Inactive Publication Date: 2017-12-19
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

From the published literature, there is no termination criterion and method to effectively solve this adaptive termination problem.

Method used

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  • Self-adaptive-termination MIMO (Multi-Input Multi-Output) radar optimization netting method in multi-surveillance area
  • Self-adaptive-termination MIMO (Multi-Input Multi-Output) radar optimization netting method in multi-surveillance area
  • Self-adaptive-termination MIMO (Multi-Input Multi-Output) radar optimization netting method in multi-surveillance area

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Embodiment

[0075] In this embodiment, the site deployment scenario is as follows Figure 6 The simulation scenario shown: two areas A and B need to be monitored, and the detection probability threshold p dt =0.8, false alarm probability p fa =10 -6 , the maximum radar detection range R max = 20km, the simulation area is a rectangle with a size of 70km×70km. According to the radar design requirements, each radar can only transmit one pulse in one observation time, and at the same time D 0 =12.5dB, σ m,n =|α| 2 , α is a Gaussian distribution with zero mean. Assuming that the number of radars J = 10, the air defense vulnerability rate of the surveillance area is used as the objective function to measure the surveillance performance of each surveillance area, which can be expressed as where f 1 (Φ) is the objective function value of the monitoring area A, f 2 (Φ) is the objective function value of the monitoring area B, and the smaller the objective function value is, the better th...

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Abstract

The invention discloses a self-adaptive-termination MIMO (Multi-Input Multi-Output) radar optimization netting method in a multi-surveillance area, and belongs to the technical field of multi-input multi-output radar netting. The method includes the following steps: S1, adopting a PSO algorithm to initialize a particle swarm, and constructing an external archive set storing non-domination particles; S2, determining a global optimal particle, updating the particle swarm, and acquiring non-domination particle swarms; S3, calculating separation distances between adjacent generations, and judging whether iterative optimization is terminated according to an iterative termination criterion; and S4, acquiring the non-domination particle swarm, and selecting a netting scheme. According to the method, an iterative calculation process can be terminated in a self-adaptive manner while an optimal optimization effect is obtained on the premise of improving surveillance performance of the multi-surveillance area, waste of time and calculation resources can be effectively reduced, and a radar optimization netting result can be quickly obtained.

Description

technical field [0001] The invention belongs to the technical field of multiple-input multiple-output radar station layout, and in particular relates to an adaptively terminated MIMO radar station layout method under multiple monitoring areas. Background technique [0002] The Multi-Input Multi-Output (MIMO) radar networking system uses the observation and judgment of multiple radars whose spatial positions are separated from each other and their coverage areas overlap each other to search, track, and identify targets in the surveillance area. Reasonable deployment of radar network can make a qualitative leap in the radar system's ability to monitor the surveillance area. Therefore, it is extremely important to study the optimal location of the radar antenna. [0003] For the research on the optimal deployment of MIMO radar, domestic and foreign research institutions have proposed many solutions. For example, A.M.Haimovich proposes a continuous exhaustive method (SEE) to s...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06N3/00
CPCG06N3/006G06Q10/04
Inventor 张天贤梁家栋王强李雪婷崔国龙孔令讲杨晓波
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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