# Sidelobe Suppression with Null Steering by Independent Weight Control

Authors: Zafar-Ullah Khan; Aqdas Naveed Malik; Fawad Zaman; Syed Azmat Hussain; Abdul-Rehman Khan
Journal: International Journal of Antennas and Propagation
 (2015)

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## Abstract

A uniform linear array ofn antenna elements can steer up to n-1 nulls. In situations where less than n-1 nulls are required to be steered, the existing algorithms have no criterion to utilize the remaining weights for sidelobe suppression. This work combines sidelobe suppression capability with null steering by independent weight control. For this purpose, the array factor is transformed as the product of two polynomials. One of the polynomials is used for null steering by independent weight control, while the second one is for sidelobe suppression whose coefficients or weights are determined by using convex optimization. Finally, a new structure is proposed to incorporate the product of two polynomials such that sidelobe suppression weights are decoupled from those of null steering weights. Simulation results validate the effectiveness of the proposed scheme.


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## Body

## 1. Introduction

Null steering for adaptive beamforming is an important area of research due to its military and commercial applications [1–6]. Null steering techniques can broadly be classified as Direction of Arrival (DOA) based beamformers and optimal adaptive beamformers [1]. Existing DOA based null steering techniques either control the excitation of elements’ amplitude only [2, 3], phase only [4, 5], or both [6]. There are also techniques that achieve null steering by changing the position and/or elevations of the array elements [7–10].Elements’ phase and amplitude excitation techniques are slow for large arrays because even if a single null changes its position, the whole set of weights is required to be reevaluated which is obviously time consuming and complicated. On the other hand, null steering by controlling the excitation amplitude only is easy to implement and less sensitive to quantization error but reduces the number of steerable nulls [2, 3]. The techniques like phase only and position perturbations of the array elements are nonlinear problems and cannot be solved directly by analytical methods [11]. Besides, position perturbations methods require servo motors for the movement of the elements and, in case of large arrays, the complexity to control element position increases due to increase in computational time to find new position perturbations.The solution for this problem is the null steering by independent weight control where if a single null changes its position, only the weight set corresponding to that null is evaluated and changed [3, 6]. Unfortunately, these DOA based beamformers do not have sidelobe suppression capability. Although this problem has been addressed for optimal adaptive beamforming algorithms [12, 13] the method cannot be used in DOA based beamformers because in these algorithms pattern synthesis weights are not determined by using optimization techniques.This paper presents a technique where the array factor is transformed as product of two polynomials such that one polynomial denoted byAF1 provides independent steering of all available nulls while the other denoted by AF2 suppresses sidelobes by utilizing remaining weights. The coefficients of AF1 are determined by forcing the zeros of AF1 to lie on unit circle in the complex plane [6] while the coefficients of AF2 are evaluated using convex optimization. Furthermore a structure is presented to implement this array factor where the sidelobe suppression weights are decoupled from the weights meant for independent null steering. Therefore the coefficients of AF2 will not be required to change with the change in position of any interference.The rest of the work is organized as follows. Section2 presents problem formulation, while proposed technique and structure are discussed in Sections 3 and 4, respectively. Simulation results are given in Section 5. Finally, conclusion and future work recommendation are given in Section 6.


## 2. Problem Formulation

Consider a uniform linear array (ULA) ofN omnidirectional elements. Let d be the element spacing, α the progressive phase, and θ the angle of arrival of the plane wave impinging on the array. Figure 1 shows the path difference of this wave on the adjacent elements of the ULA; that is, x=dcosθ. The output of the array elements is multiplied by the properly selected coefficients A0,A1,…,AN-1 to steer the nulls in the directions of interferences. We take the first element (element 0) of the array as reference and ψ=α+(2π/λ)dcosθ, where k=2π/λ is known as wave number. The signal at element 2 is the delayed version of the signal at element 1 and is expressed as ejψ. Let ejψ=z; then the array factor can be given as(1)AF1=A0+A1z+⋯+AN-1zN-1.This AF1 is the N-1-degree polynomial and has N-1 roots (nulls) dependent on coefficients A0,A1,…,AN-1. In factorized form, (1) becomes(2)AF1=z-z1z-z2⋯z-zN-1,where z1,z2,…,zN-1 are zeros forced to exist on the unit circle in the complex plane [2, 3, 6, 14] and their position on the circle depends on coefficients A0,A1,…,AN-1.Figure 1
Uniform linear array ofN elements with N-1 steerable nulls.To steer the main beam in the desired directionθs, the progressive phase shift is given by(3)α=-2πλdcos⁡θs.In order to incorporate expression (1), factors of (2) are to be multiplied iteratively by combining the coefficients of the same powers of z at each step. This process of multiplication is complicated and time consuming for large arrays. The algorithms proposed in [3, 6] avoid this multiplication by decoupling null steering weights, while the current work presents a method to add sidelobe suppression capability to these algorithms by adjusting and decoupling the weights of spare elements of the array from those of null steering weights.


## 3. Proposed Algorithm for Independent Null Steering (INS) with Suppressed Sidelobes

According to Schelkunoff [14], the product of two or more polynomials results in a polynomial and there exists a linear array corresponding to this resultant polynomial. Using the same fact, consider the desired array factor AF given below:(4)AF=AF1·AF2,where AF1 is meant for independent steering of N1 nulls and can be given as (5)AF1=∏i=1N1z-zi.The purpose of AF2 is to suppress sidelobes and it can be expressed by (6)AF2=b0+b1z+⋯+bN2-1zN2-1=sN2b,where b=[b0,b1,…,bN2-1]T represents the complex weight vector and sN2=[1,z,…,zN2-1] is the steering vector. The condition on the vector b is that it guarantees the sidelobe suppression and steers the main beam in the same direction as that of AF1. To find out b, consider a set SR that is union of two sets containing angles from the left and right sidelobe regions of the main beam with beam-width θmb; that is,(7)SR=0<θ≤θs-θmb2∪θs+θmb2<θ≤180°.Then p discrete angles are selected from SR and placed in another set ASR given by(8)ASR=θi∣θi∈SR∧θi=θ0+iδθ⊆SR,where i=0,1,…,p-1 and θ0 is the starting angle and δθ is the step size.Now consider another matrixA, containing steering vectors corresponding to the angles contained in ASR; that is,(9)A=sN2θ0sN2θ1⋯sN2θp-1T,where sN2(θi)=[1,zi,…,ziN2-1] with zi=exp(j(α+2π/λdcosθi)). Now the requirement is to minimize the array output power along the angles θi∈ASR subject to the unit output along the desired direction θs.The requirement is fulfilled if we restrict the peak output power in the sidelobe region, that is, the highest sidelobe level (HSLL) to have minimum value as shown in Figure2. Minimizing this power along the angles θi∈ASR is the same as minimizing the absolute output along these angles; that is,(10)minbmaxsN2θib,θi∈ASRsubject  tosN2θsb=1.Since the steering vectors along these angles are contained in matrix A the absolute output along these angles is the vector Ab and the above minimization problem becomes(11)minbmaxAbsubject  tosN2θsb=1.In (11) the objective function controls the sidelobe level and the constraint forms the main beam in the desired direction. This problem can be cast as the second-order cone program in the following manner:(12)Minimizetsubject  toAb≤tsN2θsb=1.The inequalities in (12) are called second-order cone constraints and (Ab,t)∈ second-order cone in Rp+1[15]. Second-order cone program is the subclass of convex optimization and hence problem (11) can be solved using [16].Figure 2
(a) Highest sidelobe level (HSLL=t) is required to be minimized when N2=6, θs=95°; (b) y=AF2 pattern when highest sidelobe level (HSLL=t) has been minimized for N2=6, θs=95°, and  θmb=24°.
(a)
(b)The polynomialAF2 suppresses sidelobe levels and has overlapping main beam with that of AF1. Due to pattern multiplication, AF=AF1·AF2 will give the independent null steering capability with suppressed sidelobes. The AF2 is required to be calculated once and remains unchanged as long as the position of the main beam is unchanged. However if the position of the main beam is changed, the coefficients of both the polynomials, that is, AF1 and AF2, will have to be recalculated and changed.


## 4. Proposed Structure

In this section, a structure is proposed to steer 5 nulls independently and to use three weights for sidelobe suppression; that is,N1=5, N2=3. This structure can easily be extended for any values of N1 and N2. The structure starts with ULA of 8 elements, that is, (N1+N2). It can be seen from Figure 3 that, for first N1 (which is 5 in this case) stages, each adder has 2 inputs. In the structure, first stage controls the position of first null where first input of each adder is multiplied by -z1. The jth output of this stage is represented by y1,j with j=1,…,N1+N2-1 and is given by(13)y1,j=zj-1z-z1forj=1,…,N1+N2-1.Similarly second stage controls second null by multiplying first input of each of its adders by -z2. These outputs are(14)y2,j=zj-1z-z1z-z2forj=1,…,N1+N2-2.It is clear from Figure 3 that we will get N2 outputs after N1 stages and these outputs will be(15)yN1,j=zj-1∏i=1N1z-zi=zj-1AF1forj=1,…,N2.It means these outputs are multiples of AF1 as shown below:(16)yN1,1,yN1,2,…,yN1,N2T=AF11,z,…,zN2-1T.Thus first N1 stages will incorporate AF1 and steer N1 nulls by independent weight control. After that the resulting N2 outputs are weighted to give AF2 for sidelobe suppression. Finally these weighted outputs are summed to result in AF=AF1·AF2 given by (17) and the corresponding structure is shown in Figure 3. Consider(17)y=AF11,z,…,zN2-1b0,b1,…,bN2-1T=AF1AF2.As mentioned earlier, convex optimization is used to find out the N2 complex weights. These N2 weights remain unchanged even if one or more nulls change their position. On the other hand, if the main beam changes its position, the whole set of weights, including INS weights for N1 stages and N2 weights for sidelobe control, is changed. Even in such situation implementation of AF1 in Figure 3 is not time consuming as compared to Figure 1, because it incorporates factors directly without multiplication and forming a single polynomial.Figure 3
Structure for independent null steering with suppressed sidelobes.


## 5. Simulation and Results

In this section, several simulation examples are carried out in MATLAB to verify the effectiveness of the proposed algorithm. In these examples element spacingd is taken as λ/2.Example 1.
This example compares the performance of the proposed technique with two algorithms, that is, INS by decoupling real weights (Realwt) and INS by decoupling complex weights (Cmplxwt). For this purpose, main beam is taken along 95°, while the four interferences are placed at 20°, 70°, 120°, and 160°. In this case, INS by decoupling real weights and INS by decoupling complex weights require ULAs having 9 and 5 elements, respectively, while the proposed algorithm is utilized using a ULA of 9 elements withN1=4 and N2=5. One can clearly see in Figure 4 that the performance of the proposed algorithm is better for sidelobe suppression as compared to the other two algorithms.Figure 4
Performance comparison of the proposed algorithm with INS by decoupling real weights (Realwt) and INS by decoupling complex weights (Cmplxwt).Example 2.
This example compares the performance of the proposed algorithm with INS by decoupling real weights when the second null is at 70° and also when it is shifted to 75°, while positions of all the other nulls remain unchanged. In Figure5, again one can see that the proposed scheme outperforms Realwt, no matter whether the second null is at 70° or is shifted to 75°. Similar behavior can be observed if the position of multiple nulls is changed.Figure 5
Performance comparison of proposed algorithm with INS by decoupling real weights [3], when second null changes its position from 70° to 75°.Example 3.
This example demonstrates the effect of number of coefficients ofAF2, that is, N2 on the sidelobe level. For this purpose sidelobe levels are compared for the same set of signals as in Example 1, when N2=4,6, and 8. It is clear from Figure 6 that the sidelobe suppression capability of the proposed algorithm increases as N2 is increased.Figure 6
Performance of proposed algorithm forN2=4, N2=6, and N2=8.Example 4.
This example shows the capability of the proposed algorithm to decouple complex weights ofAF1 to steer nulls independently. For this purpose main beam is taken along 95° and four interferences are placed at 20°, 70°, 120°, and 160°. Then the position of interferences is changed one by one and the results are shown in Table 1 where the changed position of the nulls and corresponding weights are shown by bold entries. It can easily be deduced that when any interference changes its position, only the corresponding weight is changed, while the rest of the weights remain unaffected.Table 1
Decoupling of weights by proposed algorithm for INS whenθs=95°,N1=4,N2=5.
S. number
θ
i
z
1
z
2
z
3
z
4
1
20°, 70°, 120°, 160°
-
0.9964
-
0.0842
i
0.2207
+
0.9753
i
0.2704
-
0.9627
i
-
0.8946
-
0.4469
i
2
25°, 70°, 120°, 160°
-
0.9998
+
0.0205
i
0.2207
+
0.9753
i
0.2704
-
0.9627
i
-
0.8946
-
0.4469
i
3
20°,65°, 120°, 160°
-
0.9964
-
0.0842
i
-
0.0307
+
0.9995
i
0.2704
-
0.9627
i
-
0.8946
-
0.4469
i
4
20°, 70°,125°, 160°
-
0.9964
-
0.0842
i
0.2207
+
0.9753
i
0.0426
-
0.9991
i
-
0.8946
-
0.4469
i
5
20°, 70°, 120°,155°
-
0.9964
-
0.0842
i
0.2207
+
0.9753
i
0.2704
-
0.9627
i
-
0.8429
-
0.5381
iExample 5.
This example shows the effect of change in direction of main beam onzi, b, and α. For this purpose initially main beam is taken along 95° while four interferences are placed at 20°, 70°, 120°, and 160°. Then main beam is shifted at 90° while the interferences do not change their position as given in Table 2 for both the cases. It is clear that these parameters change with the change in θs.Table 2
Effect of change inθs on different parameters.
S. number
θ
s
Parameters
Value
1
95°
b
0
-
b
4
0.0989
+
0.0098
i
,
0.2426
+
0.0120
i
,
0.3171,0.2426
-
0.0120
i
,
0.0989
-
0.0098
i
z
1
-
z
4
-
0.9964
-
0.0842
i
,
0.2207
+
0.9753
i
,
0.2704
-
0.9627
i
,
-
0.8946
-
0.4469
i
α
0.2738
2
90°
b
0
-
b
4
0.0987,0.2427,0.3172,0.2427,0.0987
z
1
-
z
4
-
0.9821
-
0.1883
i
,
0.4762
+
0.8793
i
,
0
-
i
,
-
0.9821
-
0.1883
i
α
0


## 6. Conclusion

A method for uniform linear array is proposed to steer the nulls by independent weight control and to suppress sidelobes. It uses the progressive phase shift for beam steering and product of two polynomials for independent null steering with sidelobe suppression. The zeros of independent null steering polynomial are forced to lie on the unit circle in the complex plane. Similarly, the coefficients for sidelobe suppression are determined by convex optimization. Then a structure is proposed that incorporates the product of the two polynomials. In order to steerN1 nulls independently and to use N2 weights for sidelobe suppression, a ULA of N1+N2 elements is required. In the structure, the number of weights for independent null steering and the total number of weights will be 0.5N1(N1+2N2-1) and 0.5N1(N1+2N2-1)+N2, respectively. Traditionally this array can steer N1+N2-1 nulls but the proposed technique steers only N1 nulls with suppressed sidelobes at the cost of 0.5N1(N1+2N2-1)+N2 complex weights, 0.5N1(N1+2N2-1)+1 adders, and N2-1 nulls.The coefficients for the sidelobe suppression are not affected by the change in position of one or more nulls with the condition that the main beam does not change its direction. On the other hand if the main beam changes its position, the whole set of weights of the structure along with the progressive phase shift will be changed. The sidelobes can be suppressed more by increasing the number of coefficients dedicated for this purpose.In future one can use the same approach for two- and three-dimensional arrays.



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*Source: 136826-2015-06-10.xml*