Orientation of broadband signals in telecommunication systems

Number of pages: 139 File Format: word File Code: 32232
Year: Not Specified University Degree: Master's degree Category: Electrical Engineering
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    Abstract:

    DOA Estimation for Wideband Signals

    DOA Estimation for Wideband Signals

    One ??of the most important uses of arrays is ensuring the direction of signals emitted in the environment. Many orientation methods have been used for a long time, and changes have been made in them over time. Depending on the environment, one of the orientation methods may perform better than the other methods. The important point is that most routing methods are designed for narrowband signals. In practice, the signals that exist in the environment may be broadband or they are located in different frequency ranges. One of the most common methods in the direction of broadband signals is to separate the broadband signal into different frequency ranges and then perform the necessary processing in the frequency domain. Based on this, various methods have been described for the orientation of broadband signals. In some methods, the orientation of each inter-frequency is processed independently from the other inter-spans, which are known as uncorrelated methods. Some other methods combine information from different frequency ranges and then perform orientation (correlated methods). The big problem of correlated methods is that we have to have an initial estimate of the input angles of the sources. There are also some methods whose nature is different from correlated and uncorrelated methods and it can be said that they are in between these two methods. TOPS [1] can be mentioned among these methods. which has been introduced to solve the problem of initial estimation of angles in correlated methods. The purpose of this thesis is to examine different methods of broadband signal orientation and compare the performance of each one. Different routing methods for narrowband signals are introduced and the advantages and challenges of implementing each of these algorithms are examined. (Chapter 1 and 2)

    One ??of the very important cases of signal orientation is its application in the direction of antenna radiation in order to create the maximum possible power in the direction of the target. Also, in order to orientate the targets, first of all, the angle of entry of each signal into the array should be determined. By using the concepts and methods proposed for narrowband signals and its development based on wideband signals, in the third chapter, various wideband algorithms and their classification will be introduced. One of the most common methods in the direction of broadband signals is to separate the broadband signal into different frequency ranges and then perform the necessary processing in the frequency domain. Based on this, various methods have been described for the orientation of broadband signals. In some methods, the orientation of each inter-frequency is processed independently from the other inter-spans, which are known as uncorrelated methods. Some other methods combine information from different frequency ranges and then perform orientation (correlated methods). The big problem of correlated methods is that we have to have an initial estimate of the input angles of the sources. There are also some methods whose nature is different from correlated and uncorrelated methods and it can be said that they are in between these two methods (Chapter 4). Among these methods, TOPS [2] can be mentioned [16], which was introduced to solve the problem of initial estimation of angles in correlated methods. In the last chapter, using MATLAB simulation, we will implement correlated and uncorrelated algorithms and examine the results and challenges raised. Based on this, first we will explain the scalar propagation field [1] of array antennas and then we will introduce narrow band signals and finally we will define the antenna array model in the transmission of wide bandwidth signals (broadband signal).

    1-2- Wave propagation

    As we know, based on Maxwell's equation, the wave propagation function is a variable of time and space. Therefore, the wave equation of electromagnetic signals according to Maxwell's equation is defined as follows: (1-1) where electric field strength, wave propagation speed, Laplacian operator (1-2) The location vector is defined. After being applied as a general scalar field, the equation of the transmitted wave signal at time t and the location is calculated based on the following equation: rtl;">                        (1-4)

    By substituting equation (1-4) in equation (1-3), the following expression is obtained:

    (1-5)                                               

    For all values, , that are true in the above equation, the answer The wave equation can be displayed in the following polar form. (1-6) where the wave number vector and the exponential function are called monochromatic wave plane function[2]. The scalar field can be expressed as a combination of all wave planes for all frequencies as follows [1]: (1-7) where (1-8) rtl;"> and considering that

    (1-9)                                              .

    according to the relationship (1-5); The phase value in relation (1-6) will be as follows:

    (1-11)

    Usually, the direction and speed of propagation are introduced by a vector (slowness vector[3]). According to the above relations, it is clear that the size of the vector is equal to the reciprocal of the propagation speed. Using spherical coordinates as shown in the figure (1-1)
    can be displayed as follows:

    (1-12) rtl;">(1-13)                      

    where S( ) is the Fourier transform of the function.

  • Contents & References of Orientation of broadband signals in telecommunication systems

    List:

     

    Abstract 1

    Introduction. 2

                                  

    Chapter One: Principles of Wave Propagation

    1-1- Introduction. 4

    1-2- Propagation of waves. 4

    1-3-array sensors. 6

    1-4- linear array signal processing. 7

    1-4-1- basic assumptions. 7

    1-4-1-1- far field 7

    1-4-1-2- narrowband signal. 7

    1-4-1-3- stationary. 8

    1-4-1-4- multiple signals. 8

    1-4-1-5- Noise 8

    1-5- Space-time conversion. 9

    1-6- Random signals. 10

     

    Chapter Two: narrowband signal processing methods

    2-1-Introduction. 15

    2-2-spectrum-based methods. 15

    2-3-Beam shaping methods. 15

    2-3-1-Conventional beam shaping method. 15

    2-3-2- Capone method. 17

    2-3-3- Methods based on subspace 19

    2-3-4-Method introduction. 20

    2-3-5- Algorithm. 21

    2-3-6- Introducing the method. 23

    2-3-7- data model 25

    2-3-8- ESPIRIT algorithm. 28

    2-4-array antennas. 31

    2-5- signal model. 35

    2-6- Covariance matrix. 36

     

    Chapter Three: Routing Broadband Signals

    3-1- Introduction. 39

    3-2- Introduction of broadband signals. 39

    3-3- Introduction of different techniques for directing broadband signals. 41

    3-3-1- Broadband data modeling. 41

    3-3-2- Brief introduction of broadband signal routing methods using filter banks. 42

    3-3-3- Broadband signal frequency model. 44

    3-3-4- Different algorithms for routing broadband signals. 47

    3-3-5- uncorrelated orientation methods. 47

    3-3-6- frequency uncorrelated methods. 48

    3-3-7- Forming fear by Capon method. 48

    3-3-8- Arithmetic averaging. 51

    3-3-9- Geometric averaging method. 52

    3-3-10- Harmonic averaging method. 53

    3-3-11- Broadband music algorithm. 53

    3-3-12- Appropriate weighting algorithm of subspaces 55

    3-3-13- Calculating estimation by method. 58

    3-3-14- Practical considerations in the method. 60

    3-3-15- subspace correlated orientation methods ( ) 62

    3-3-16- diagonal concentration matrix method. 62

    3-3-17- Method of rotating signal subspace. 64

    3-3-18- Using focal matrix in the method. 66

    3-3-19- Average weighting method for signal subspaces ( ) 67

    Chapter four: TOPS algorithm

    4-1- Introduction. 70

    4-2- Basic concepts. 70

    4-3- Presentation of a mathematical model. 71

    4-4- Algorithm development to multidimensional space. 76

    4-5- Image along the signal subspace. 78

    4-6- Calculation algorithm. 80

    4-6-1- Complexity of calculations. 81

    Chapter V: Simulation of DOA estimation algorithms

    for linear arrays. 83

    5-1- Introduction. 84

    5-2- Estimation algorithms. 84

    5-2-1- Brief introduction of algorithms used in simulation. 84

    5-2-1-1- Review of MUSIC and Capon algorithm. 85

    5-2-1-2- Signal subspace correlation algorithm ( ) 86

    5-2-1-3- Signal focal subspace matrix ( ) 88

    5-2-1-3-1- Method calculation algorithm. 89

    5-2-1-3-2-Important points in calculating the estimation method. 90

    5-3- Data modeling 91

    5-3-1- Characteristics of the source of the transmitted signal. 91

    5-3-2- Assumptions of the data received by the antenna array. 92 5-4- Simulated scenarios.

    References. 121

    Abstract 1

    Introduction. 2

                                  

    Chapter One: Principles of Wave Propagation

    1-1- Introduction. 4

    1-2- Propagation of waves. 4

    1-3-array sensors. 6

    1-4- linear array signal processing. 7

    1-4-1- basic assumptions. 7

    1-4-1-1- far field 7

    1-4-1-2- narrowband signal. 7

    1-4-1-3- stationary. 8

    1-4-1-4- multiple signals. 8

    1-4-1-5- Noise 8

    1-5- Space-time conversion. 9

    1-6-. 9

    1-6- Random signals. 10

     

    Chapter Two: narrowband signal processing methods

    2-1-Introduction. 15

    2-2-spectrum-based methods. 15

    2-3-Beam shaping methods. 15

    2-3-1-Conventional beam shaping method. 15

    2-3-2- Capone method. 17

    2-3-3- Methods based on subspace 19

    2-3-4-Method introduction. 20

    2-3-5- Algorithm. 21

    2-3-6- Introducing the method. 23

    2-3-7- data model 25

    2-3-8- ESPIRIT algorithm. 28

    2-4-array antennas. 31

    2-5- signal model. 35

    2-6- Covariance matrix. 36

     

    Chapter Three: Routing Broadband Signals

    3-1- Introduction. 39

    3-2- Introduction of broadband signals. 39

    3-3- Introduction of different techniques for directing broadband signals. 41

    3-3-1- Broadband data modeling. 41

    3-3-2- Brief introduction of broadband signal routing methods using filter banks. 42

    3-3-3- Broadband signal frequency model. 44

    3-3-4- Different algorithms for routing broadband signals. 47

    3-3-5- uncorrelated orientation methods. 47

    3-3-6- frequency uncorrelated methods. 48

    3-3-7- Forming fear by Capon method. 48

    3-3-8- Arithmetic averaging. 51

    3-3-9- Geometric averaging method. 52

    3-3-10- Harmonic averaging method. 53

    3-3-11- Broadband music algorithm. 53

    3-3-12- Appropriate weighting algorithm of subspaces 55

    3-3-13- Calculation of estimation by method. 58

    3-3-14- Practical considerations in the method. 60

    3-3-15- subspace correlated orientation methods ( ) 62

    3-3-16- diagonal concentration matrix method. 62

    3-3-17- Method of rotating signal subspace. 64

    3-3-18- Using focal matrix in the method. 66

    3-3-19- Average weighting method for signal subspaces ( ) 67

    Chapter four: TOPS algorithm

    4-1- Introduction. 70

    4-2- Basic concepts. 70

    4-3- Presentation of a mathematical model. 71

    4-4- Algorithm development to multidimensional space. 76

    4-5- Image along the signal subspace. 78

    4-6- Calculation algorithm. 80

    4-6-1- Complexity of calculations. 81

    Chapter V: Simulation of DOA estimation algorithms

    for linear arrays. 83

    5-1- Introduction. 84

    5-2- Estimation algorithms. 84

    5-2-1- Brief introduction of algorithms used in simulation. 84

    5-2-1-1- Review of MUSIC and Capon algorithm. 85

    5-2-1-2- Signal subspace correlation algorithm ( ) 86

    5-2-1-3- Signal focal subspace matrix ( ) 88

    5-2-1-3-1- Method calculation algorithm. 89

    5-2-1-3-2-Important points in calculating the estimation method. 90

    5-3- Data modeling 91

    5-3-1- Characteristics of the transmitted signal source. 91

    5-3-2- Assumptions of the data received by the antenna array. 92

    5-4- Simulated scenarios. 92

    5-4-1- Scenario No. 1. 92

     

    Chapter Six: Conclusion and Suggestions

    6-1- Conclusion. 122

    6-2- Suggestions. 123

    References. 121

     

     

     

    Source:

    Stoica, P., and R. Moses, Spectral Analysis of Signals, Prentice Hall, 2005.

    Roy, R., and T. Kailath, “ESPRIT-Estimation of Signal Parameters Via Rotational Invariance Techniques,” IEEE Trans. on Signal Processing, Vol. 37, No. 7, July 1989, pp. 984–995.

    Schmidt, R., ‘‘Multiple Emitter Location and Signal Parameter Estimation,’’ IEEE Trans.on Antennas and Propagation, Vol. AP-34, No. 3, March 1986, pp. 276–280.

    Zatman, M., ‘‘How Narrow Is Narrowband?’’ IEE Proc.-Radar, Sonar Navig., Vol. 145, No. 2, April 1998, pp. 85–91.

    Chandran, S., and M. K. Ibrahim, ``DOA Estimation of Wide-Band Signals Based on Time-Frequency Analysis,'' IEEE J. of Oceanic Engineering, Vol. 24, No. 1, January 1999, pp. 116–121.

    Wax, M., and T. Kailath, ``Spatio-Temporal Spectral Analysis by Eigen-Structure Methods,'' IEEE Trans. on Acoustics, Speech, and Signal Processing, Vol. ASSP-32, No. 4, August 1984, pp. 817–827.

    Wang, H.

Orientation of broadband signals in telecommunication systems