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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 42495 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Behnia, F
- Abstract:
- MIMO radar is a next generation radar which transmits arbitrary waveforms at each one of its apertures. It has been shown that design of waveforms for MIMO radars in order to synthesize a desired spatial beampattern, is mapped into a waveform correlation matrix (R) design in the narrowband case. Therefore, waveform design in MIMO radar for beamforming could be broken into two steps, namely correlation matrix design and waveform synthesis for achieving given R. As of now, given a desired beampattern or estimated location information of targets, calculating R has been modeled as an optimization problem like SDP. Also, in some special cases like rectangular beampattern, close form solutions for R has been proposed. In this paper, we introduce a fast algorithm which is capable of designing R in order to achieve more arbitrary beampatterns. Our proposed algorithm is based on eigenvalue decomposition of correlation matrix which employs neither an optimization nor an iteration process. Furthermore, the proposed algorithm leads to uniform elemental power, low sidelobe level and decorrelation of targets which is a great boon, looking from both the hardware and software perspectives. Waveform synthesis is also a constraint optimization problem. Practical requirements imposed on waveforms generated are low peak to average power ratio and good cross and auto correlation properties. In addition to these requirements, the proposed algorithm for waveform synthesis must consume relatively low CPU time, a point which is of prime importance in applications needing large number of samples like synthetic aperture radars. In this paper we propose a novel stochastic method based on copulas for constant modulus waveform synthesis to obtain a given correlation matrix. These waveforms are easy to generate with no numerical optimization involved and with added benefit of having low correlation side lobe levels in order of LS algorithms. The new waveform synthesis algorithms also make it possible to generate a wide range of orthogonal to coherent waveforms from finite or infinite alphabets
- Keywords:
- Waveform Synthesis ; Eigenvalue Decomposition ; Multiple Input Multiple Output (MIMO)System ; Beamforming ; Copulas
Digital Object List-
محتواي پايان نامه - view
Bookmark- فصل 1: فصل 1
- مقدمه‌اي بر رادار
- فصل 2: فصل 2
- مروري بر مفاهیم پايه و بیان مسئله
- فصل 3: فصل 3
- مروری بر روشهای شکلدهی پرتو توان
- 3-1- روشهای طراحی ماتریس همبستگی شکلموج
- 3-2- روشهای سنتز شکلموج برای ساخت ماتریس همبستگی
- 3-2-1- روش سنتز کمینه مربعات خطا
- (3-13) =
- (3-14) 1 L H = 1 2 H
- (3-15) min ||− 1 2 || 2 ∈ × ;∈ ×
- (3-16) = =+1 ∗ − = ∗ ()
- (3-17) m=1 n=1 p=−P+1,p≠0 −1 r mn p =small
- (3-18) ∗ = 1 (1) ⋯ 1 () ⋯ 0 ⋱ ⋱ ⋮ 1 (1) 1 () ⋮ (1) ⋯ () ⋯ 0 ⋱ ⋱ (1) () +−1
- (3-19) | ∗ − | 2 =""
- (3-20) min || − 1 2 || 2
- (3-21) || − 1 2 || 2 =−2{ ∗ )
- (3-22) 1 2 ∗ = ∗
- (3-23) = ∗
- شکل (3-2) پرتوتوان شکلموجهای طراحی شده با روش کمینه مربعات خطا[10]
- شکل (3-3) تابع خودهمبستگی شکلموجهای طراحی شده با روش کمینه مربعات خطا(بدون در نظر گرفتن تاخیر زمانی)[10]
- شکل (3-4) تابع خودهمبستگی شکلموجهای طراحی شده با روش کمینه مربعات خطا(با در نظر گرفتن تاخیر زمانی)[10]
- 3-2-2- سنتز پارامتری با شکل موجهای Dirichlet
- 3-2-3- روش CAN برای شکل موجهای عمود
- 3-2-4- روش نگاشت مستقیم متغیرهای گوسی DGRVM
- 3-2-1- روش سنتز کمینه مربعات خطا
- 3-3- روش های ترکیبی
- فصل 4: فصل 4
- روش پیشنهادی طراحی ماتریس همبستگی به منظور شکلدهی پرتوتوان
- 4-1- مقدمه
- 4-2- قضایای بنیادی
- 4-3- مجموعه نمونههای فضایی متعامد OSS
- (4-7) = [ 1 ′ 2 ′ ⋯ ′ ]
- (4-8) = Where =( 1 , 2 ,⋯, )
- (4-9) ′ = ′ ′ =
- (4-10) = 1 1 ′ ∗ 1 ′ +⋯+ ′ ∗ ′
- (4-11) () = ∗ () + ∗ ()
- (4-12) = cos 0 sin 2 2 sin ⋮ −1 −1 sin
- (4-13) () | = ′ = ( ∗ ′ ′ + ∗ ( ′ )( ′ ))=0
- (4-14) ( ′ )= 1 ′
- (4-15) ′ = max ( +1 ′ − ′ )
- (4-16) ′ = −1 2− 1 ′ (∈ ,∈[− 1− sin 1 ′ 2 , 1+ sin 1 ′ 2 )
- (4-17) ′ = min +1 ′ − ′ = min ( −1 +2 − −1 ( ))
- (4-18) 2− 1 ′ =−1
- (4-19) 1 ′ = −1 2+1 ∈ و ∈[− +1 2 , −1 2 ]
- (4-20) ∗ = = −1 2+1 =− +1 2 ,− −1 2 +1,⋯, −3 2 }
- (4-21) min ′ ′ = ∗
- (4-22) ∗ = = −1 2+2− , =0,1,⋯,−1 }
- (4-23) ∗ = ∗ باشد فرد اگر ∗ = باشد زوج اگر
- (4-24) = −1 2
- شکل (4-1) مقدار بهره رزلوشن حریصانه مجموعه OG-OSS را نسبت BS-OSS
- شکل (4-2) نمونههاي فضايي را براي تعداد آنتنهاي متفاوت روي دو مجموعهي BS-OSS و OG-OSS
- 4-4- الگوریتمEVD برای طراحی ماتریس همبستگی شکلموج
- 4-5- اصلاح ماتریس همبستگی شکل موج با روش BDOS
- فصل 5: فصل ۵
- روش پیشنهادی سنتز شکلموج به منظور تحقق ماتریس همبستگی
- فصل 6: فصل ۶
- نتایج عددی
- 6-1- مقدمه
- 6-2- طراحی ماتریس همبستگی برای شکلدهی پرتو توان
- 6-3- سنتز شکل موج برای تحقق ماتریس همبستگی
- (6-1) 2 = − 2 2 | − ∗ () () | 2 cos()
- (6-2) =( | − | 2 +2 =1 −1 | | 2 )/ 2
- (6-3) 1 2 = =+1 1 2 ∗ −
- (6-4) = 11 () ⋯ 1 () ⋮ ⋱ ⋮ 1 () ⋯ ()
- (6-5) 2 − 2 2 cos =1
- (6-6) || +1 − || 2 ≤0.1
- شکل (6-9) خطاي فضايي وزن‌دهي شده‌ي، تحقق پرتو توان برای سیگنالینگ متعامد
- شکل (6-10) norm برای سیگنالینگ متعامد
- شکل (6-11) SLL روش های گوناگون سنتز شکل موج متعامد
- شکل (6-12) تابع خودهمبستگی روشهای گوناگون سنتز شکل موج همدوس
- شکل (6-13) تابع همبستگی متقابل روشهای گوناگون سنتز شکل موج همدوس
- شکل (6-14) چگالي فاز شكلموجها در روش DGRVM
- شکل (6-15) پرتوتوان در مدل اتورگرسیو
- شکل (6-16) خطاي فضايي وزن‌دهي شده‌ي، تحقق پرتو توان برای روش DC-FGM
- شکل (6-17) خطاي فضايي وزن‌دهي شده‌ي، تحقق پرتو توان برای روش IC-quadratic
- شکل (6-18) خطاي فضايي وزن‌دهي شده‌ي، تحقق پرتو توان برای سیگنالینگ همبسته
- شکل (6-19) SLL تابع خودهمبستگی در سیگنالینگ BPSK متعامد
- شکل (6-20) SLL تابع همبستگی متقابل در سیگنالینگ BPSK متعامد
- شکل (6-21) خطاي فضايي وزن‌دهي شده‌ي، تحقق پرتو توان برای سیگنالینگ همبستهBPSK
- 6-4- روش های وفقی در رادارهای MIMO
- شکل (6-22) بلوک دیاگرام رادارهایMIMO از ديد روش‌هاي وقفي
- شکل (6-23) عملکرد الگوریتمهای وفقی در رادارهای MIMO
- فصل 7: فصل ۷
- نتیجه گیری و کارهای آتی
- جدول (7-1) روشهای پیشنهادی سنتز شکلموج
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