基于TDOA與GROA的多運(yùn)動(dòng)站誤差配準(zhǔn)算法

孫順; 董凱; 齊林; 劉俊

doi:10.11999/JEIT160562

基于TDOA與GROA的多運(yùn)動(dòng)站誤差配準(zhǔn)算法

doi: 10.11999/JEIT160562

孫順¹,
董凱¹,
齊林¹,
劉俊¹

基金項(xiàng)目:

國(guó)家自然科學(xué)基金(61471379, 61102166, 91538201)

計(jì)量
- 文章訪問(wèn)數(shù): 1410
- HTML全文瀏覽量: 162
- PDF下載量: 260
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2016-05-28
- 修回日期: 2017-05-02
- 刊出日期: 2017-06-19

Multiple Moving Observers Registration Algorithm Based on TDOA and GROA

Funds:

The National Natural Science Foundation of China (61471379, 61102166, 91538201)

摘要

摘要: 針對(duì)多運(yùn)動(dòng)站無(wú)源定位過(guò)程中存在系統(tǒng)誤差的問(wèn)題，該文提出一種基于到達(dá)時(shí)差(TDOA)與到達(dá)增益比(GROA)最小二乘配準(zhǔn)算法。該算法利用泰勒展開(kāi)把非線性的量測(cè)方程線性化，利用最小二乘算法得到對(duì)目標(biāo)狀態(tài)和系統(tǒng)誤差的聯(lián)合估計(jì)，并考慮了量測(cè)噪聲和站址誤差的影響。同時(shí)推導(dǎo)了存在量測(cè)噪聲、站址誤差和系統(tǒng)誤差時(shí)的克拉美羅下界(CRLB)，并分析了系統(tǒng)誤差對(duì)CRLB的影響。多種條件下的仿真表明，該算法對(duì)系統(tǒng)誤差和目標(biāo)狀態(tài)的估計(jì)精度較高，說(shuō)明了算法的有效性。
- 無(wú)源定位 /
- 誤差配準(zhǔn) /
- 多運(yùn)動(dòng)站 /
- 到達(dá)時(shí)差 /
- 到達(dá)增益比
Abstract: This paper proposes a least-squares registration algorithm using Time Differences Of Arrival (TDOA) and Gain Ratios Of Arrival (GROA) measurements to solve the problem of multiple moving observers passive localization under the influence of system error. The proposed algorithm linearizes the nonlinear measurement equation by Taylor expansion, executes least squares algorithm for the joint estimation of target state and system biases, and considers the influence of measurement noise and location errors of observers. Meanwhile Cramr-Rao Lower Bound (CRLB) under the influence of measurement noise, location errors of observers and system biases is derived, and the influence of system error on CRLB is analyzed. Simulations under several different conditions indicate the proposed algorithm is valid, which can effectively estimate the system biases and target state.
- Passive localization /
- Registration /
- Multiple moving observers /
- Time Differences Of Arrival (TDOA) /
- Gain Ratios Of Arrival (GROA)

HTML全文

參考文獻(xiàn)(24)

何友, 修建娟, 張晶煒, 等. 雷達(dá)數(shù)據(jù)處理及應(yīng)用 [M]. 第2版, 北京: 電子工業(yè)出版社, 2009: 209-210.

HE You, XIU Jianjuan, ZHANG Jingwei, et al. Radar Data Processing With Applications [M]. Second Edition, Beijing: Publishing House of Electronics Industry, 2009: 209-210.

CHEN J C, YIP L, ELSON J, et al. Coherent acoustic array processing and localization on wireless sensor networks[J]. Proceedings of the IEEE, 2003, 91(8): 1154-1162. doi: 10.1109/ JPROC.2003.814924.

房嘉奇, 馮大政, 李進(jìn). 穩(wěn)健收斂的時(shí)差頻差定位技術(shù)[J]. 電子與信息學(xué)報(bào), 2015, 37(4): 798-803. doi: 10.11999/ JEIT140560.

FANG Jiaqi, FENG Dazheng, and LI Jin. A robustly convergent algorithm for source localization using time difference of arrival and frequency difference of arrival[J]. Journal of Electronics Information Technology, 2015, 37(4): 798-803. doi: 10.11999/JEIT140560.

HATEM H and KUTLUYIL D. Passive localization of scanning emitters[J]. IEEE Transactions on Aerospace and Electronic Systems, 2010, 46(2): 944-951. doi: 10.1109/TAES. 2010.5461671.

HO K C and SUN M. Passive source localization using time differences of arrival and gain ratios of arrival[J]. IEEE Transactions on Signal Processing, 2008, 56(2): 464-477. doi: 10.1109/TSP.2007.906728.

ZHU Hongyan and WANG Chen. Joint track-to-track association and sensor registration at the track level[J]. Digital Signal Processing, 2015, 41: 48-59. doi: 10.1016/j.dsp. 2015.03.012.

董凱, 王海鵬, 劉瑜. 基于拓?fù)浣y(tǒng)計(jì)距離的航跡抗差關(guān)聯(lián)算法[J]. 電子與信息學(xué)報(bào), 2015, 37(1): 50-55. doi: 10.11999/ JEIT140244.

DONG Kai, WANG Haipeng, and LIU Yu. Anti-bias track association algorithm based topology statistical distance[J]. Journal of Electronics Information Technology, 2015, 37(1): 50-55. doi: 10.11999/JEIT140244.

胡振濤, 胡玉梅, 張瑾, 等. 基于CKF的系統(tǒng)誤差與目標(biāo)狀態(tài)聯(lián)合估計(jì)算法[J]. 光電子激光, 2015, 26(3): 535-540. doi: 10.16136/j.joel.2015.03.0500.

HU Zhentao, HU Yumei, Zhang Jin, et al. Joint estimation of system error and state based on cubature Kalman filter[J]. Journal of Optoelectronics Laser, 2015, 26(3): 535-540. doi: 10.16136/j.joel.2015.03.0500.

NICKENS O and BRANKO R. Maximum likelihood registration for multiple dissimilar sensors[J]. IEEE Transactions on Aerospace and Electronic Systems, 2003, 39(3): 1074-1083. doi: 10.1109/TAES.2003.1238759.

吳衛(wèi)華, 江晶. WGS-84坐標(biāo)系下多空基無(wú)源傳感器最大似然配準(zhǔn)[J]. 系統(tǒng)工程與電子技術(shù), 2015, 37(2): 304-309. doi: 10.3969/j.issn.1001-506X.2015.02.12.

WU Weihua and JIANG Jing. Maximum likelihood registration for passive sensors of multiple airborne platforms in WGS-84[J]. Systems Engineering and Electronics, 2015, 37(2): 304-309. doi: 10.3969/j.issn.1001-506X.2015.02.12.

董云龍, 何友, 王國(guó)宏, 等. 基于ECEF的廣義最小二乘誤差配準(zhǔn)技術(shù)[J]. 航空學(xué)報(bào), 2006, 27(3): 463-467.

DONG Yunlong, HE You, WANG Guohong, et al. Generalized least squares registration algorithm with Earth-Centered Earth-Fixed (ECEF) corrdinate system[J]. Acta Aeronautica Et Astronautica Sinica, 2006, 27(3): 463-467.

曲長(zhǎng)文, 王昌海, 徐征. 基于NLS的多機(jī)只測(cè)角誤差配準(zhǔn)算法[J]. 信號(hào)處理, 2012, 28(4): 533-538.

QU Changwen, WANG Changhai, and XU Zheng. NLS-based registration algorithm for bearings-only location by multiple airborne observers[J]. Signal Processing, 2012, 28(4): 533-538.

CHAN Y T and RUDNICKI S W. Bearings-only and doppler-bearing tracking using instrumental variables[J]. IEEE Transactions on Aerospace and Electronic Systems, 1992, 28(4): 1076-1082.

MOTTI G and ELI F. Effect of bias on bearing-only target location[J]. IEEE Transactions on Aerospace and Electronic Systems, 1990, 26(1): 22-25. doi: 10.1109/7.53410.

HO K C, LU Xiaoning, and KOVAVISARUCH L. Source localization using TDOA and FDOA measurements in the presence of receiver location errors analysis and solution[J]. IEEE Transactions on Signal Processing, 2007, 55(2): 684-696. doi: 10.1109/TSP.2006.885744.

張賢達(dá). 矩陣分析與應(yīng)用 [M]. 第2版, 北京: 清華大學(xué)出版社, 2013: 54-61.

ZHANG Xianda. Matrix Analysis and Applications [M]. Second Edition, Beijing: Tsinghua University Press, 2013: 54-61.

相關(guān)文章

施引文獻(xiàn)

資源附件(0)

訪問(wèn)統(tǒng)計(jì)