A Knowledge-Aided STAP Approach with Effective Color Loading Factors

GAO Yong-chan; LIAO Gui-sheng; ZHU Sheng-qi; YANG Dong

doi:10.3969/j.issn.0372-2112.2012.10.033

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A Knowledge-Aided STAP Approach with Effective Color Loading Factors

更新时间：2025-07-16

- A Knowledge-Aided STAP Approach with Effective Color Loading Factors
- Acta Electronica Sinica Vol. 40, Issue 10, Pages: 2101-2106(2012)
- 作者机构：
  
  西安电子科技大学雷达信号处理国家重点实验室,陕西,西安,710071
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2012.10.033
  CLC： TN957.51
- Published：2012
- 稿件说明：
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GAO Yong-chan, LIAO Gui-sheng, ZHU Sheng-qi, et al. A Knowledge-Aided STAP Approach with Effective Color Loading Factors[J]. Acta Electronica Sinica, 2012, 40(10): 2101-2106.
DOI：

GAO Yong-chan, LIAO Gui-sheng, ZHU Sheng-qi, et al. A Knowledge-Aided STAP Approach with Effective Color Loading Factors[J]. Acta Electronica Sinica, 2012, 40(10): 2101-2106. DOI： 10.3969/j.issn.0372-2112.2012.10.033.

摘要

针对非均匀杂波环境里独立同分布训练样本较少的问题

本文提出了一种知识辅助的LCMV-STAP方法.该方法首先求解出知识辅助的LCMV-STAP模型中的权矢量表达式

然后推导出色加载因子与约束常数的关系式

最后求解出两个色加载因子.仿真结果表明

与传统STAP方法相比

知识辅助的LCMV-STAP方法在非均匀杂波环境下仍能获得较好的输出信干噪比

自适应匹配滤波器检测目标的概率优于传统STAP方法.

Abstract

There are not adequate independent and identically distributed training samples under a heterogeneous clutter environment.Thus

this paper proposes a knowledge-aided LCMV-STAP approach.Firstly

the weight of knowledge-aided LCMV-STAP model is solved

and then the formula of the relationship between the color loading factors and the constraint constants is derived.Finally

the two color loading factors are solved.The computer simulations show that knowledge-aided LCMV-STAP has a better output signal-interference noise ratio than the traditional approach under a heterogeneous clutter environment

and the detection probability of Adaptive Matched Filter is higher than that of the traditional approach.

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