陳顯寧,萬(wàn) 群,楊萬(wàn)麟
(電子科技大學(xué)電子工程學(xué)院 成都 610054)
循環(huán)與非循環(huán)混合信號(hào)源快速DOA估計(jì)與識(shí)別方法
陳顯寧,萬(wàn) 群,楊萬(wàn)麟
(電子科技大學(xué)電子工程學(xué)院 成都 610054)
在日益復(fù)雜的信號(hào)環(huán)境中,陣列信號(hào)處理需要面對(duì)循環(huán)和非循環(huán)混合信號(hào)源的情況越來(lái)越多。針對(duì)循環(huán)和非循環(huán)混合信號(hào)源的情況,分析了混合信號(hào)源條件下的子空間特征,提出了一種混合信號(hào)源條件下的快速波達(dá)方向估計(jì)與識(shí)別方法,有效地利用了混合信號(hào)源中的非循環(huán)特性。理論分析和仿真實(shí)驗(yàn)結(jié)果表明,波達(dá)方向估計(jì)結(jié)果的分辨率不僅較于常規(guī)方法有所提高,而且可處理的信源數(shù)目大于陣元數(shù)目,具有較強(qiáng)的過(guò)載處理能力。
循環(huán)信號(hào); 波達(dá)方向估計(jì); 識(shí)別; 混合信號(hào)源; 非循環(huán)信號(hào)
陣列信號(hào)處理一般都假設(shè)陣元接收的信號(hào)來(lái)自循環(huán)信號(hào)源,即用復(fù)平面上的一點(diǎn)表示任意時(shí)刻信號(hào)包絡(luò)的正交I/Q分量時(shí),隨著時(shí)間的變化,信號(hào)包絡(luò)的軌跡是繞復(fù)平面原點(diǎn)循環(huán)變化的[1-3]。但實(shí)際上常出現(xiàn)非循環(huán)信號(hào)源情況,如智能天線采用BPSK、MSK等調(diào)制方式的通信信號(hào)源[4],隨著時(shí)間的變化,信號(hào)包絡(luò)的正交I/Q分量的軌跡是通過(guò)復(fù)平面原點(diǎn)的一條線段。
最近,利用信號(hào)源的時(shí)域非循環(huán)特性改進(jìn)信號(hào)源參數(shù)估計(jì)性能的研究越來(lái)越多,如非循環(huán)信號(hào)源波達(dá)方向估計(jì)的根MUSIC方法[5]和增強(qiáng)型酉ESPRIT方法[6]、非循環(huán)信號(hào)源頻偏估計(jì)的增強(qiáng)型盲方法[7]和無(wú)數(shù)據(jù)輔助的方法[8]、非循環(huán)信號(hào)源的盲分離方法[9]、非循環(huán)調(diào)制的OFDM信號(hào)峰均比抑制[10]等。這些研究與利用信號(hào)源時(shí)域上其他較復(fù)雜特性(如有限符號(hào)集信息)的空時(shí)聯(lián)合信號(hào)處理方法相比,利用信號(hào)源的時(shí)域非循環(huán)特性的方法比較簡(jiǎn)單,也能獲得較明顯的性能增強(qiáng)效果。
實(shí)際上,民用無(wú)線通信和無(wú)線電對(duì)抗環(huán)境中的信號(hào)源十分復(fù)雜,往往不是單一的循環(huán)信號(hào)源或非循環(huán)信號(hào)源,因此,有必要研究利用混合信號(hào)源特性的參數(shù)估計(jì)與識(shí)別方法。本文針對(duì)循環(huán)和非循環(huán)混合信號(hào)源,提出了一種增強(qiáng)型的波達(dá)方向估計(jì)方法和識(shí)別循環(huán)與非循環(huán)信號(hào)源的方法,并給出了仿真結(jié)果。
實(shí)驗(yàn) 1 假設(shè)有由6個(gè)間隔為半波長(zhǎng)的陣元組成的均勻線陣,3個(gè)等功率的信號(hào)源的波達(dá)方向分別為0.01、0.11、0.15 rad,空間噪聲為高斯白噪聲,信噪比為30 dB,快攝數(shù)為100。
假設(shè)第2個(gè)和第3個(gè)信號(hào)源是非循環(huán)信號(hào)源,第1個(gè)信號(hào)源是循環(huán)信號(hào)源,100次試驗(yàn)的估計(jì)結(jié)果如圖1所示,圖中實(shí)線為本文方法結(jié)果,虛線為常規(guī)方法結(jié)果。由圖1可見(jiàn):(1)在循環(huán)信號(hào)源的波達(dá)方向處,本文提出的改進(jìn)的ESPRIT方法得到兩組相近的估計(jì)結(jié)果,可以作為區(qū)分非循環(huán)信號(hào)源和循環(huán)信號(hào)源的標(biāo)準(zhǔn);(2)本文方法提供了比常規(guī)的ESPRIT方法更為準(zhǔn)確的估計(jì)。
圖1 3個(gè)信號(hào)源時(shí)本文方法和常規(guī)方法100次試驗(yàn)的估計(jì)結(jié)果比較
實(shí)驗(yàn) 2 在保持其他條件不變的條件下,圖2a和圖2b分別給出了本文方法和常規(guī)的ESPRIT方法對(duì)第二個(gè)到達(dá)角估計(jì)結(jié)果的RMSE隨SNR和陣元數(shù)的變化的性能曲線(對(duì)應(yīng)每個(gè)參數(shù)進(jìn)行1 000次獨(dú)立實(shí)驗(yàn))??梢?jiàn)本文方法的估計(jì)性能明顯優(yōu)于常規(guī)ESPRIT方法。
實(shí)驗(yàn) 3 同樣假設(shè)有由 6個(gè)間隔為半波長(zhǎng)的陣元組成的均勻線陣,3個(gè)等功率的循環(huán)信號(hào)源的波達(dá)方向分別為?0.6、?0.4、0.2 rad,4個(gè)等功率的非循環(huán)信號(hào)源的波達(dá)方向分別為?0.2、0、0.4和0.6 rad,信噪比為25 dB,快攝數(shù)為200。100次試驗(yàn)的估計(jì)結(jié)果如圖3所示,圖中實(shí)線為本文方法結(jié)果,虛線為常規(guī)方法結(jié)果。由圖可見(jiàn):(1)常規(guī)方法由于信號(hào)源數(shù)大于陣元數(shù),所以最多只能估計(jì)5個(gè)結(jié)果,且估計(jì)結(jié)果偏差較大;(2)在循環(huán)信號(hào)源的波達(dá)方向處,本文方法得到了兩組相近的估計(jì)結(jié)果,可以作為識(shí)別循環(huán)信號(hào)源的標(biāo)準(zhǔn);(3)本文方法在信號(hào)源數(shù)大于陣元數(shù)時(shí)依然能夠提供準(zhǔn)確的估計(jì),具有較強(qiáng)的信源過(guò)載能力。
圖2 本文方法和常規(guī)方法的估計(jì)性能比較
圖3 7個(gè)信號(hào)源時(shí)本文方法和常規(guī)方法100次試驗(yàn)的估計(jì)結(jié)果比較
與針對(duì)單一的循環(huán)或非循環(huán)信號(hào)源的陣列信號(hào)處理不同,本文研究了循環(huán)和非循環(huán)混合信號(hào)源的波達(dá)方向估計(jì)問(wèn)題和這兩種信號(hào)源的識(shí)別問(wèn)題,利用混合信號(hào)源的子空間特性推導(dǎo)并提出了增強(qiáng)型空間譜估計(jì)方法,該方法不僅具有較高的分辨率,容易識(shí)別該兩種信號(hào)源,而且具有較強(qiáng)的信源過(guò)載能力。
[1]CHARG P, WANG Y, SAILLARD J. Non circular sources direction finding method using polynomial rooting[J].Signal Processing, Elsevier Science Publishers, 2001, 81:1765-1770.
[2]PICINBONO B. On circularity[J]. IEEE Trans SP, 1994,42(12): 3473-3482.
[3]PICINBONO B, CHEVALIER P. Widely linear-estimation with complex data[J]. IEEE Trans SP, 1995, 43(8):2030-2033.
[4]ABEIDA H, DELMAS J P. Stochastic Cramer-Rao bound of DOA estimates for non-circular Gaussian signals[C]//IEEE International Conference on Acoustics, Speech, and Signal Processing. [S.l.]: IEEE, 2004.
[5]CHARGE P, WANG Y, SAILLARD J. A root-music algorithm for non circular sources[C]//IEEE International Conference on Acoustics, Speech, and Signal Processing.[S.l.]: IEEE, 2001.
[6]HAARDT M, ROMER F. Enhancements of unitary ESPRIT for non-circular sources[C]//IEEE International Conference on Acoustics, Speech, and Signal Processing. [S.l.]: IEEE,2004.
[7]CIBLAT P, SERPEDIN E, WANG Y. A fractionallysampling based frequency offset enhanced blind estimator for non-circular transmissions[C]//Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers. [S.l.]: [s.n.], 2002.
[8]CIBLAT P, LOUBATON P, SERPEDIN E, et al.Performance of non-data aided carrier offset estimation for non-circular transmissions through frequency-selective channels[C]//IEEE International Conference on Acoustics,Speech, and Signal Processing. [S.l.]: IEEE, 2000.
[9]GALY J, ADNET C. Blind separation of non-circular sources[C]//Proceedings of the Tenth IEEE Workshop on Statistical Signal and Array Processing. [S.l.]: IEEE, 2000.
[10]WANG H, CHEN B. On the distribution of peak-toaverage power ratio for non-circularly modulated OFDM signals[C]//Global Telecommunications Conference. [S.l.]:[s.n.], 2003.
編 輯 稅 紅
Fast Direction of Arrival Estimation and Identification of Mixed Circular and Non-Circularity Sources
CHEN Xian-ning, WAN Qun, and YANG Wan-lin
(School of Electronic Engineering, University of Electronic Science and Technology of China Chengdu 610054)
In array signal processing, the cases of mixed circular and non-circular sources are more and more frequently encountered in complex signal situation. By analyzing the subspace property of the mixed circular and non-circular signal sources in detail, an enhanced and fast method for direction of arrival (DOA)estimation and identification of mixed circular and non-circular sources is proposed. Since the proposed method efficiently utilizes the useful non-circularity properties of the mixed circular and non-circular source model, it has better performance of DOA estimation compared with the method only based on homogeneous source model and its performance is closed to the theoretical bound. Simulation results show that by using the proposed method in DOA estimation, the number of mixed signal sources can be larger than the number of array elements.
circular source; direction of arrival; identification; mixed source; non-circular source
TN911.7
A
10.3969/j.issn.1001-0548.2010.06.003
2009- 04- 09;
2010- 03- 22
國(guó)家自然科學(xué)基金(60372022);新世紀(jì)優(yōu)秀人才支持計(jì)劃(NCET-05-0806)
陳顯寧(1977- ),男,博士生,主要從事陣列信號(hào)處理、波達(dá)方向估計(jì)方面的研究.