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1 Introduction
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Digital Mobile TV (DMTv) is a radio signal that is received in a mobile environment. Its channel characteristics are very complex, especially in urban environments where the TV signal received on a fast-moving vehicle can fade up to several tens of times within 1 s. This fading phenomenon seriously deteriorates the quality of the received signal and affects the reliability of signal reception. For car TVs, to maintain acceptable transmission quality under such propagation conditions, multiple anti-fading techniques must be employed.
Smart antenna technology is a kind of airspace signal processing technology. For example, using smart antennas for vehicle HDTV combined with time domain signal processing can not only resist fading, multipath resistance, and anti-interference, but also make full use of multipath signals to greatly improve signal reception. Reliability [1-2].
2 Smart Antenna Algorithm
The most representative of the adaptive algorithms are the LMS algorithm and the HA algorithm. In order to achieve adaptive anti-jamming, the LMS algorithm needs to have a reference signal. If the output of the array is directly used as the error signal, the pursuit of minimum mean square error will result in the smallest array output. This is called the "power inversion algorithm" [3]. The power inversion algorithm uses a minimum power criterion with strict constraints. The criterion requires that the power vector is adjusted to a certain extent, and the power of the output is minimized to achieve the purpose of self-adaptation. The minimum power criterion is essentially the linear constrained minimum variance (LCMV) criterion, and its mathematical expression is
The significance is to minimize the total output power under the condition that the gain of the useful signal s is constant. It is actually equivalent to maximizing the output signal-to-noise ratio.
The basic idea of the power inversion method is to keep the output power of the first branch array element constant, and the weighting coefficients of other array elements can be adjusted, and the power output of the array element is minimized by adjusting other weighting coefficients. Since the output power of one array element is constant, when the weighting coefficient is adjusted to minimize the output power, the physical meaning is that the interference direction in the pattern will form a null trap, and the stronger the interference, the deeper the zero trap.
2.1 Establishment of algorithm model
The D interferences are respectively incident from different directions θ1, θ2, ..., θd to the M-ary uniform linear array with the spacing d=λ/2, λ is the working wavelength, and θ1, θ2 are the interference incident directions. Then the received array vector is X(t)=AS(t)+n(t) (3)
Where: X(t) is the received vector; S(t) is the received signal; n(t) is the background noise; A is the array steering vector matrix. Have
A=[a(θ1), a(θ2),...,a(θn)] (4)
Where: a(θn) represents the steering vector of the pth interference; p∈[1,D] and
Where: φp = πsin θp.
Define the covariance matrix of the input signal as
Where: P = E{s(t)sH(t)} is the correlation matrix of the signal, σ2 is the noise power, and [·]H represents the conjugate transpose of the matrix. 2.2 Algorithm Derivation The power inversion adaptive algorithm is essentially an adaptive algorithm with strict constraints. The constraint condition is WTSo=1, which means that the adaptive matrix needs to ensure the antenna gain of the θo direction is 1 at any time.
So=[1,O,...,0]T (7)
Then the condition WT·So=1 becomes
[W1, W2,...,WN][1,0,...,0]T=l (8)
Or W1=1 (9)
That is, the weighting coefficient of the first branch is required to be 1. This adaptive array is shown in Figure 1. In the figure, xi(t) is the signal received by each array element, and the vector is expressed as
X=(x1,x2,...,xM)T (10)
Wi is a multi-weighting coefficient, written as
W=(Wl,W2,...,WM)
Where W1=1, the array output is
Y=WTX ten XTW (12)
Select the optimum value of (W2, W3..., WN)T to minimize the array output E[|y|]. Therefore, it is imaginable in the physical sense that its beam pattern will introduce zero-sag in the direction of interference, and the stronger the interference, the deeper the indentation, and the corresponding optimal output is the smallest. This is what power inversion means.
Array output power Poup. Can be expressed as [3]
Add the constraint WTSo=1 to form the Lagrang function
Take the gradient of formulas (2) to (12),
Optimal weight vector
Where: is the autocorrelation matrix of the input vector X, the superscript * indicates conjugate, the superscript T indicates matrix transposition, and the input is Lagrangian multiplier coefficient.
Minimum output power is
Where: X' is the input vector of the adjustable portion of the array, Z is X' and the fixed branch input x. Correlation vector, and R' is the correlation matrix of X', so Rxx can be expressed as a block matrix
Where: P1 is the input power of the fixed branch. The optimal weight vector can be expressed as
among them The best weight vector for the tunable portion of the array.
Substituting equation (5), equation (19), and equation (20) into equation (14)
Expandable
That is, the optimal weight vector equation of the power inversion adaptive algorithm.
3 simulation and implementation
Real-time updating of antenna weights is realized by DSP. Currently, the development of DSP applications is mostly written in a combination of high-level languages and high-level languages. The Matlab simulation results of the power inversion algorithm are shown in Figure 2.
Figures 2 and 3 show the simulation results of three interfering signals at different horizontal and elevation angles when the desired signal is (15°, 30°). The directions of the three interfering signals are: (10°, 25°), (40°, 180°), (75°, 300°), it can be seen that the interference signals in all three directions are attenuated to a small value, which also shows the effectiveness of the algorithm.
After adopting the smart antenna technology, the system can form the zero point of the pattern in the interference direction within a few milliseconds, thereby effectively suppressing the influence of the pulse interference on the signal reception, and greatly improving the signal receiving performance.
June 28, 2024
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June 28, 2024
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