乘性噪聲背景下基于非線性漸消濾波的單信標(biāo)測距定位算法

朱子堯; 韓樹平; 郭正東; 劉建波

doi:10.11999/JEIT180239

乘性噪聲背景下基于非線性漸消濾波的單信標(biāo)測距定位算法

doi: 10.11999/JEIT180239 cstr: 32379.14.JEIT180239

海軍潛艇學(xué)院 ??青島 ??266044

詳細(xì)信息

作者簡介:
朱子堯：男，1992年生，博士生，研究方向為水下定位與導(dǎo)航、水聲信號處理

韓樹平：男，1965年生，教授，博士生導(dǎo)師，研究方向為聲吶裝備技術(shù)及應(yīng)用、水聲信號處理

郭正東：男，1977年生，副教授，研究方向為水下定位與導(dǎo)航、水下航行器航行安全

劉建波：男，1986年生，博士生，研究方向為水聲通信、水聲信號處理、水下定位與導(dǎo)航

通訊作者:
朱子堯　zzylecture@163.com

中圖分類號: TB568
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- 文章訪問數(shù): 2080
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- PDF下載量: 58
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2018-03-16
- 修回日期: 2018-07-17
- 網(wǎng)絡(luò)出版日期: 2018-07-30
- 刊出日期: 2019-01-01

Single Beacon Location Algorithm Based on Nonlinear Fading Filter Under Multiplicative Noise Background

Navy Submarine Academy, Qingdao 266044, China

摘要

摘要:
針對基于加性噪聲模型的單信標(biāo)測距定位算法不能精確表征距離觀測量的實際特征，存在模型失配的問題，該文給出一種考慮乘性噪聲特性的聯(lián)合最小二乘法和非線性漸消濾波的兩步定位算法。在分析有效聲速誤差與距離觀測量乘性噪聲內(nèi)在聯(lián)系的基礎(chǔ)上，建立了乘性噪聲背景下的測距誤差模型，通過引入一種新的弱化因子計算方法對乘性噪聲背景下帶單重漸消因子的非線性漸消濾波算法進(jìn)行了改進(jìn)，利用基于最小二乘法的預(yù)定位過程解決改進(jìn)算法對初值敏感的問題。仿真及試驗數(shù)據(jù)表明該算法在水下航行器接近信標(biāo)的態(tài)勢下定位精度明顯優(yōu)于加性噪聲背景下的擴展卡爾曼濾波算法。
- 單信標(biāo)測距定位 /
- 乘性噪聲 /
- 漸消因子 /
- 非線性濾波 /
- 有效聲速
Abstract:
Single beacon location algorithm based on additive noise model can not accurately represent the actual characteristics of distance measurement, leading to a problem of model mismatch. A two step location algorithm considering the multiplicative noise characteristics is presented, which combines least squares algorithm and nonlinear fading filter. A range error model in the background of multiplicative noise is established based on the analysis of the effective sound velocity error. The nonlinear fading filtering algorithm with single fading factor under multiplicative noise background is improved by introducing the attenuation factor which increases the track continuity. Using the least squares based pre-location process to solve the problem that the improved algorithm is sensitive to the initial value. The simulation and experimental data show that the location precision of the proposed algorithm is obviously better than the extended Kalman filtering algorithm under the additive noise background.
- Single beacon localization /
- Multiplicative noise /
- Fading factor /
- Nonlinear filtering /
- Effective sound speed

HTML全文

圖 1 水下單信標(biāo)同步式測距定位模型

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圖 2 航跡起始點散布區(qū)域示意圖

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圖 3 水下航行器運動軌跡

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圖 4 ISFEKF算法對乘性噪聲參數(shù)敏感性仿真

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圖 5 定位誤差比較

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圖 6 試驗數(shù)據(jù)處理結(jié)果

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