基于稀疏重建的大型陣列天線綜合
發(fā)布時(shí)間：2018-08-25 09:46
【摘要】：大型陣列天線由于具有增益高、波瓣寬度窄、波束控制能力強(qiáng)等優(yōu)點(diǎn),在現(xiàn)代雷達(dá)及無(wú)線通信系統(tǒng)中得到了越來(lái)越廣泛的研究與應(yīng)用。同時(shí),工程中為了降低成本和系統(tǒng)復(fù)雜度,一般希望將大型陣列設(shè)計(jì)成稀疏陣或子陣形式。然而,現(xiàn)有的設(shè)計(jì)方法在大型陣列應(yīng)用中還面臨著一些挑戰(zhàn)。本文從實(shí)際應(yīng)用需求出發(fā),圍繞大型陣列設(shè)計(jì)中的幾個(gè)關(guān)鍵技術(shù)展開(kāi)了研究,包括:稀疏陣列綜合、基于方向圖可重構(gòu)天線的大間距陣和稀疏陣設(shè)計(jì)以及子陣合成,著重研究了稀疏重建在大型陣列天線綜合中的應(yīng)用。主要內(nèi)容分以下五個(gè)部分:1.基于壓縮感知理論的稀疏陣列綜合方法從稀疏信號(hào)重建的角度審視了稀疏陣列綜合問(wèn)題,建立了基于壓縮感知(CS)理論的稀疏陣列綜合模型,將最大化稀疏陣列綜合問(wèn)題轉(zhuǎn)化為線性約束下的稀疏重建問(wèn)題。在此基礎(chǔ)上,提出了一種基于欠定系統(tǒng)局域解法(FOCUSS)的綜合方法,該方法可以智能地確定實(shí)現(xiàn)期望方向圖所需的最小陣元個(gè)數(shù)、陣元的位置和激勵(lì),并且對(duì)稀疏線陣、面陣以及共形陣綜合都適用。2.基于多測(cè)量向量協(xié)同稀疏重建的多方向圖稀疏陣列綜合方法提出了一種基于多測(cè)量向量欠定系統(tǒng)局域解法(M-FOCUSS)的多方向圖稀疏陣列綜合方法。該方法基于多測(cè)量向量協(xié)同稀疏重建(MMVCSR)理論,采用協(xié)同綜合策略解決了傳統(tǒng)方法在處理多方向圖問(wèn)題時(shí)出現(xiàn)的不同方向圖的陣元位置分布不統(tǒng)一的問(wèn)題。接著,將M-FOCUSS方法與有源方向圖(AEP)技術(shù)合理結(jié)合,從而將實(shí)際陣列的互耦影響考慮到了稀疏陣列優(yōu)化設(shè)計(jì)中。數(shù)值仿真和實(shí)物測(cè)試證明了該方法的有效性。3.基于擾動(dòng)壓縮采樣的大型稀疏陣列快速綜合方法首先,提出了一種基于擾動(dòng)壓縮采樣(PCS)的稀疏陣列綜合方法,該方法通過(guò)向傳統(tǒng)的壓縮感知理論模型中引入陣元位置擾動(dòng)變量,建立了一種連續(xù)的陣元位置優(yōu)化模型,擴(kuò)展了問(wèn)題的優(yōu)化空間,同時(shí)減少了網(wǎng)格劃分,大大提高了算法的優(yōu)化效果和計(jì)算效率。接著,針對(duì)針對(duì)陣元位置擾動(dòng)引起的近似誤差問(wèn)題,提出了一種擴(kuò)展的擾動(dòng)壓縮采樣(EPCS)方法,采用二級(jí)網(wǎng)格策略有效降低了標(biāo)準(zhǔn)PCS的建模誤差和計(jì)算復(fù)雜度。然后,為解決PCS和EPCS算法在處理復(fù)值問(wèn)題時(shí)陣元位置出現(xiàn)虛部的問(wèn)題,提出了一種基于稀疏重建和局部?jī)?yōu)化的交替迭代算法,并用于復(fù)激勵(lì)的多方向圖稀疏面陣綜合。最后,研究了PCS方法在可掃描大型稀疏陣列低副瓣綜合中的應(yīng)用,并對(duì)稀疏陣的陣元縮減比與掃描范圍和陣列口徑的關(guān)系進(jìn)行了分析。4.基于方向圖可重構(gòu)天線的大間距陣和稀疏陣設(shè)計(jì)首先,提出了一種可實(shí)現(xiàn)二維圓極化波束切換的方向圖可重構(gòu)天線。然后,將方向圖可重構(gòu)天線分別用于矩形柵格大間距陣、三角柵格大間距陣以及大型隨機(jī)稀疏陣設(shè)計(jì)中,實(shí)驗(yàn)結(jié)果表明,與傳統(tǒng)陣列相比,基于此天線設(shè)計(jì)的陣列在陣元縮減比、波束掃描范圍、掃描增益和副瓣電平性能上具有明顯優(yōu)勢(shì)。5.均勻子陣的柵瓣抑制針對(duì)均勻子陣的柵瓣抑制問(wèn)題,提出了一種基于波束指向不相同子陣模塊和開(kāi)關(guān)控制的柵瓣抑制方法,通過(guò)優(yōu)化子陣方向圖的波束指向,并在陣列掃描過(guò)程中有選擇地激勵(lì)部分子陣,使均勻子陣等效為一個(gè)子陣方向圖各不相同的且激活子陣布局隨掃描角變化的非均勻稀疏子陣。仿真結(jié)果表明,該方法可以實(shí)現(xiàn)對(duì)柵瓣電平的有效抑制,得到的子陣級(jí)陣列可保持與同口徑陣元級(jí)相控陣相當(dāng)?shù)牟ò陮挾?且盡管與陣元級(jí)相控陣相比,增益有所下降,但通道數(shù)的減少更加可觀。
[Abstract]:Large array antennas have been widely studied and applied in modern radar and wireless communication systems because of their advantages such as high gain, narrow lobe width and strong beam control ability. At the same time, in order to reduce cost and system complexity, it is generally hoped to design large array into sparse array or sub-array. There are still some challenges in the application of the design method in large-scale arrays.In this paper, several key techniques in large-scale array design are studied, including sparse array synthesis, large-spacing array and sparse array design based on pattern reconfigurable antenna, and sub-array synthesis. The main contents are as follows: 1. Sparse array synthesis method based on compressed sensing theory examines sparse array synthesis problem from the point of sparse signal reconstruction, establishes sparse array synthesis model based on compressed sensing (CS) theory, transforms the problem of maximizing sparse array synthesis into one of maximizing sparse array synthesis. On this basis, a synthesis method based on under-determined system local solution (FOCUSS) is proposed. This method can intelligently determine the minimum number of elements needed to realize the desired pattern, the position and excitation of the elements, and is applicable to the synthesis of sparse linear, planar and conformal arrays. 2. Based on multiple measurements A new method of multi-directional pattern sparse array synthesis based on M-FOCUSS is proposed. This method is based on the theory of multi-vector cooperative sparse reconstruction (MMVCSR), and the traditional method is solved by the cooperative synthesis strategy. Then, the M-FOCUSS method is combined with the active pattern (AEP) technique reasonably, so that the mutual coupling effect of the actual array is taken into account in the sparse array optimization design. Numerical simulation and experimental results show that the method is effective. Firstly, a novel sparse array synthesis method based on perturbation compressed sampling (PCS) is proposed. By introducing the perturbation variables into the traditional compressed sensing model, a continuous optimization model of array position is established, which expands the optimization space of the problem and decreases the optimization space at the same time. Secondly, an extended perturbation compression sampling (EPCS) method is proposed to reduce the modeling error and computational complexity of standard PCS. Secondly, the modeling error and computational complexity of PCS and EPCS are reduced effectively to solve the approximate error caused by the position perturbation of array elements. An alternating iterative algorithm based on sparse reconstruction and local optimization is proposed for complex excitation sparse array synthesis. Finally, the application of PCS method in scannable large sparse array synthesis with low sidelobes is studied, and the sparse array elements are reduced. The relationship between the ratio and the scanning range and the array aperture is analyzed. 4. Based on the large spacing array and sparse array design of pattern reconfigurable antenna, a pattern reconfigurable antenna is proposed to realize two-dimensional circularly polarized beam switching. The experimental results show that the array based on this antenna has obvious advantages over traditional arrays in terms of element reduction ratio, beam scanning range, scanning gain and sidelobe level performance. 5. The grating lobe suppression of uniform subarray is proposed for the problem of grating lobe suppression of uniform subarray. By optimizing the beam direction of the subarray pattern and selectively exciting some subarrays in the scanning process of the array, the uniform subarray is equivalent to an inhomogeneous sparse subarray with different subarray pattern and different activation subarray layout varying with scanning angle. The real results show that this method can effectively suppress the grating lobe level, and the subarray array can maintain the same lobe width as the element-level phased array with the same aperture.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN820
本文編號(hào)：2202504
[Abstract]:Large array antennas have been widely studied and applied in modern radar and wireless communication systems because of their advantages such as high gain, narrow lobe width and strong beam control ability. At the same time, in order to reduce cost and system complexity, it is generally hoped to design large array into sparse array or sub-array. There are still some challenges in the application of the design method in large-scale arrays.In this paper, several key techniques in large-scale array design are studied, including sparse array synthesis, large-spacing array and sparse array design based on pattern reconfigurable antenna, and sub-array synthesis. The main contents are as follows: 1. Sparse array synthesis method based on compressed sensing theory examines sparse array synthesis problem from the point of sparse signal reconstruction, establishes sparse array synthesis model based on compressed sensing (CS) theory, transforms the problem of maximizing sparse array synthesis into one of maximizing sparse array synthesis. On this basis, a synthesis method based on under-determined system local solution (FOCUSS) is proposed. This method can intelligently determine the minimum number of elements needed to realize the desired pattern, the position and excitation of the elements, and is applicable to the synthesis of sparse linear, planar and conformal arrays. 2. Based on multiple measurements A new method of multi-directional pattern sparse array synthesis based on M-FOCUSS is proposed. This method is based on the theory of multi-vector cooperative sparse reconstruction (MMVCSR), and the traditional method is solved by the cooperative synthesis strategy. Then, the M-FOCUSS method is combined with the active pattern (AEP) technique reasonably, so that the mutual coupling effect of the actual array is taken into account in the sparse array optimization design. Numerical simulation and experimental results show that the method is effective. Firstly, a novel sparse array synthesis method based on perturbation compressed sampling (PCS) is proposed. By introducing the perturbation variables into the traditional compressed sensing model, a continuous optimization model of array position is established, which expands the optimization space of the problem and decreases the optimization space at the same time. Secondly, an extended perturbation compression sampling (EPCS) method is proposed to reduce the modeling error and computational complexity of standard PCS. Secondly, the modeling error and computational complexity of PCS and EPCS are reduced effectively to solve the approximate error caused by the position perturbation of array elements. An alternating iterative algorithm based on sparse reconstruction and local optimization is proposed for complex excitation sparse array synthesis. Finally, the application of PCS method in scannable large sparse array synthesis with low sidelobes is studied, and the sparse array elements are reduced. The relationship between the ratio and the scanning range and the array aperture is analyzed. 4. Based on the large spacing array and sparse array design of pattern reconfigurable antenna, a pattern reconfigurable antenna is proposed to realize two-dimensional circularly polarized beam switching. The experimental results show that the array based on this antenna has obvious advantages over traditional arrays in terms of element reduction ratio, beam scanning range, scanning gain and sidelobe level performance. 5. The grating lobe suppression of uniform subarray is proposed for the problem of grating lobe suppression of uniform subarray. By optimizing the beam direction of the subarray pattern and selectively exciting some subarrays in the scanning process of the array, the uniform subarray is equivalent to an inhomogeneous sparse subarray with different subarray pattern and different activation subarray layout varying with scanning angle. The real results show that this method can effectively suppress the grating lobe level, and the subarray array can maintain the same lobe width as the element-level phased array with the same aperture.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN820
【參考文獻(xiàn)】
相關(guān)期刊論文 前9條
1 王繼新;;從“谷歌地球”看俄“頓河”雷達(dá)陣地[J];兵器知識(shí);2015年02期
2 魯加國(guó);汪偉;齊美清;;星載SAR相控陣天線柵瓣抑制技術(shù)[J];微波學(xué)報(bào);2013年Z1期
3 趙菲;齊會(huì)穎;邱磊;柴舜連;毛鈞杰;;自適應(yīng)動(dòng)態(tài)Meta粒子群優(yōu)化算法綜合多方向圖共形陣列[J];電子與信息學(xué)報(bào);2012年06期
4 王文昌;李雷;劉春靜;劉楓;;基于粒子群優(yōu)化算法的非均勻子陣波束形成技術(shù)[J];電子信息對(duì)抗技術(shù);2010年01期
5 焦永昌;楊科;陳勝兵;張福順;;粒子群優(yōu)化算法用于陣列天線方向圖綜合設(shè)計(jì)[J];電波科學(xué)學(xué)報(bào);2006年01期
6 張玉洪;;非均勻間隔稀布陣列的旁瓣電平限制[J];西安電子科技大學(xué)學(xué)報(bào);1992年04期
7 張玉洪,保錚;加權(quán)直線天線陣的最佳稀布[J];電子學(xué)報(bào);1990年05期
8 張玉洪,保錚;最佳非均勻間隔稀布陣列的研究[J];電子學(xué)報(bào);1989年04期
9 張玉洪;保錚;;任意分布陣列天線波束寬度的精確估計(jì)[J];西安電子科技大學(xué)學(xué)報(bào);1988年02期
相關(guān)會(huì)議論文 前1條
1 白雪;張小苗;楊倩;趙旭東;;用遺傳算法綜合具有三種方向圖的可重構(gòu)陣列天線[A];2009年全國(guó)天線年會(huì)論文集（下）[C];2009年
相關(guān)博士學(xué)位論文 前1條
1 陳客松;稀布天線陣列的優(yōu)化布陣技術(shù)研究[D];電子科技大學(xué);2006年
相關(guān)碩士學(xué)位論文 前1條
1 王茂澤;二維寬帶寬角掃描相控陣天線研究[D];西安電子科技大學(xué);2014年
，本文編號(hào)：2202504
本文鏈接：http://sikaile.net/kejilunwen/xinxigongchenglunwen/2202504.html
最近更新
教材專著
