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Improved multi-extended target tracking method

A multi-expansion target and target technology, applied in the power control field of conventional peak shaving of public buildings, can solve problems such as measurement data loss, improve tracking performance, improve target tracking accuracy, solve measurement data loss and computational complexity The effect of degree optimization problem

Inactive Publication Date: 2018-08-21
NANJING UNIV OF SCI & TECH
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Problems solved by technology

[0005] In view of the above problems, the present invention proposes an improved multi-extended target tracking method to solve the problems of multi-extended target measurement set division, measurement data loss and computational complexity optimization in the actual radar measurement information, and improve the multi-extended target tracking. performance

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Embodiment Construction

[0024] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0025] 1. Clustering: clustering and dividing the measurement data set of the sensor.

[0026] The method for clustering and dividing the measurement data set of the sensor in the present invention is the DBSCAN algorithm.

[0027] First, initialize two parameters of the DBSCAN algorithm, namely ε (radius parameter) and MinPts (neighborhood density threshold).

[0028] The ε neighborhood of the object p refers to: any data object p in the data space (measurement data set in the present invention), and its ε neighborhood is a collection of objects in a circular area with p as the center and ε as the radius , denoted as

[0029] Nε(p)={q|q∈D^d(p,q)<ε}

[0030] where D is the measurement data set, d(p,q) is the distance between object p and point q;

[0031] The core object refers to: if the ε neighborhood of the object p contains at least MinPts objects, the object p is a...

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Abstract

The invention discloses an improved multi-extended target tracking method, which comprises the steps of 1, clustering; 2, initialization; 3, predicting and updating; 4, pruning and merging; and 5, repeating the step 3 and the step 4. In allusion to a multi-extended target tracking problem in a clutter environment, measurement data of extended targets is effectively processed through adopting a DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, and effective tracking for the multiple extended targets is realized. Due to the introduction of a scale factor and the design of an adaptive threshold, the precision loss caused by a blind area of radar is reduced, the calculation amount of a filter is reduced, and the engineering application of a GM-CPHD filter is facilitated.

Description

technical field [0001] The invention belongs to the technical field of smart grids, in particular to a power consumption control method for realizing conventional peak regulation in public buildings where electric vehicles participate. Background technique [0002] With the widespread application of high-resolution sensors, the study of Extended Target Tracking (ETT) technology has become a hot spot. In particular, with the continuous improvement of radar resolution, multiple measurements of the same target with different equivalent scattering centers can be received at each moment. At this time, the target is no longer a point target, but an extended target. In recent years, Professor Ronald P.S. Mahler has proposed a probability hypothesis density (Probability Hypothesis Density, PHD) filtering algorithm based on random finite set (RFS) theory, which can simultaneously realize the target number and target state without considering data association estimate. It first trac...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S13/72
CPCG01S13/726
Inventor 吴盘龙邓宇浩何山王雪冬肖仁强曹竞丹
Owner NANJING UNIV OF SCI & TECH
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