基于角度-多普勒相关系数的低维时空自适应处理

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本文献标题"Reduced-dimension space-time adaptive processing based on angle-Doppler correlation coefficient"聚焦于雷达信号处理领域的创新方法，特别是用于解决空间时间自适应处理（Space-Time Adaptive Processing, STAP）中的复杂性和数据量问题。传统的STAP技术在抑制空中雷达的杂波干扰方面表现出色，但其计算需求高且需要大量辅助数据，这在实时应用中构成挑战。为了降低计算负担并提高效率，研究者提出了一个基于角度-多普勒相关系数（Angle-Doppler Correlation Coefficient, ADC2）的降维STAP（Reduced-Dimensional STAP, RD-STAP）算法。该算法的核心思想是通过预先估计杂波的傅里叶基向量，构建ADC2参数来评估每个辅助通道在消除干扰方面的有效性。ADC2作为衡量指标，能够帮助选择最优的降维通道组，即使在有限的自由度（Degrees of Freedom, DOF）条件下，也能实现最佳的检测性能。算法的关键步骤包括： 1. **杂波基向量预估**：在离线阶段，通过对历史数据进行分析，计算出代表杂波特征的基向量，这些基向量反映了杂波在角度和多普勒频谱上的特性。 2. **ADC2构建**：利用这些基向量，计算每个辅助通道与杂波基向量的相关性，形成ADC2，反映通道在抑制特定角度和多普勒频率下的杂波能力。 3. **辅助通道选择**：通过ADC2评估，选择一组性能最优的辅助通道，这些通道可以有效地抵消或减小杂波的影响，同时保持所需的计算资源在可接受范围内。 4. **固定通道数下的最佳性能**：由于采用ADC2作为决策依据，即使在DOF受限的情况下，算法也能保证在有限的辅助通道数量下获得最佳的干扰抑制效果。这种新型的RD-STAP方法不仅提高了雷达系统的实时性和鲁棒性，还通过减少计算复杂度，对于资源有限或者实时性强的环境具有重要意义。它可能在现代军事、航空和自动驾驶等领域得到广泛应用，为雷达系统的性能优化提供了新的解决方案。

EURASIP Journal on Advances

in Signal Processing

Li et al. EURASIP Journal on Advances in Signal

Processing

(2016) 2016:97

DOI 10.1186/s13634-016-0395-2

RESEARCH Open Access

Reduced-dimension space-time adaptive

processing based on angle-Doppler

correlation coefficient

Ruiyang Li

, Jun Li, Wei Zhang and Zishu He

Abstract

Traditional space-time adaptive processing (STAP) is a strategy for clutter suppression in airborne radar, which

requires a large number of computational complexity and secondary data. In order to address the problem,

reduced-dimension (RD) STAP is generally used. We propose a novel RD STAP through searching the best channels as

the auxiliary channels to cancel the interference. Based on the estimation of the clutter Fourier basis vectors offline, a

parameter named angle-Doppler correlation coefficient (ADC

) is constructed to evaluate the capability of each

auxiliary channel in clutter suppression, and the best sets of RD channels can be selected. The proposed algorithm can

achieve the best detection performance with the fixed number of auxiliary channel. When the degrees of freedom

(DOF) are restricted to a small value, only one auxiliary channel is needed to guarantee the SINR loss less than 3 dB.

Therefore, the requirement of the training sample can be reduced, which makes the proposed approach more

suitable for the heterogeneous clutter environments.

Keywords: Airborne radar, Space-time adaptive processing, Reduced-dimension, Clutter covariance matrix

1 Introduction

Space-time adaptive processing (STAP) plays an impor-

tant role in the areas of airborne radar and sonar systems,

which collect signals linearly from an array to detect weak

targets within severe clutter and jamming environments

[1, 2]. The clutter-plus-noise covariance matrix (CCM) is

employed to calculate the filter weights for clutter sup-

pression. It has been long known that increasing the

number of degrees of freedom (DOF) enables excellent

detection performance, but since the computational com-

plexity and the number of samples for estimation CCM

are limited, it is difficult to be implemented in practical

work [3]. In recent years, a large amount of productive

works have been studied aiming at STAP with few DOF

and secondary data and provide a better detection per-

formance in heterogeneous clutter and strong jammer

environment, including the knowledge-aided radar, the

multiple-input multiple-output radar, and the jamming

suppression in complex environment [4–6].

*Correspondence: realowen10@foxmail.com

School of Electronic Engineering, University of Electronic Science and

Technology of China (UESTC), 611731 Chengdu, People’s Republic of China

The foremost theory of STAP is to adjust the space-time

filter weights to maximize output signal-to-interference-

plus-noise ratio (SINR) adaptively with DOF as less

as possible. Therefore, the dimensionality reduction

and rank reduction techniques are explored extensively

and addressed in the literature. When it comes to

reduced-dimension (RD) STAP, some typical suboptimal

approaches like the factor approach [7], the joint domain

localized (JDL) [8], and the space-time multiple-beam

(STMB) [9] have been proposed, which employ a fixed

dimension reducing transformation prior to the process-

ing. Lately, a modified RD STAP was proposed by select-

ing auxiliary channels near the clutter ridge [10]. However,

none of the traditional RD STAP can select auxiliary

channels adaptively. A multistage multiple-beam (MSMB)

technique is proposed in [11, 12], based on the principle

of selecting auxiliary channels to cancel the interference

components in the main channel clearly. But it is not

appropriate for engineering applications because a large

amount of calculation is needed.

On the other hand, reduced-rank (RR) STAP

approaches make use of data-dependent transformations,

such as the principal components (PC) inverse [13], the

International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and

reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the

Creative Commons license, and indicate if changes were made.

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