A Novel Iterative Inner-Pulse Integration Target Detection Method for Bistatic Radar

双基地雷达 啁啾声 计算机科学 雷达 脉冲多普勒雷达 匹配滤波器 连续波雷达 多普勒效应 雷达成像 滤波器(信号处理) 声学 算法 物理 光学 计算机视觉 电信 激光器 天文
作者
Tong Ding,Juan Zhang,Shiyang Tang,Linrang Zhang,Yachao Li
出处
期刊:IEEE Transactions on Geoscience and Remote Sensing [Institute of Electrical and Electronics Engineers]
卷期号:60: 1-15 被引量:5
标识
DOI:10.1109/tgrs.2022.3186012
摘要

A large time-bandwidth product bistatic radar offers several advantages in high-resolution target detection and motion parameter estimation, but the scale factor and inner-pulse Doppler will also be introduced in the radar echoes when detecting high-speed targets. Under this condition, the conventional matched filter will cause a certain energy loss and a non-negligible shift of the range center, which is called mismatch effect. Considering the special geometries of the bistatic radar, we first establish the precise echo signal model to describe the radar echoes for high-speed targets in a space-air based bistatic radar system. By analyzing the mismatch effect within the pulse and the migration between pulses, we have obtained the mathematic relationship between the scale factor, inner-pulse Doppler shift, range, equivalent velocity and accelerate. Following that, we perceive that the parameters of the matched filter are related to the target motion parameters, i.e., a priori unknown, which inspires us to propose an iterative coherent integration method to achieve the intra-pulse and inter-pulse integration. A precise echo signal model matched filter with initial parameters is defined and a roughly motion parameter estimation is acquired by the precise echo signal model-based Keystone transform and inner-pulse chirp Fourier transform. The estimated parameters are used for matched filter construction and coherent integration. This process is performed over multiple iterations to provide an accurate motion parameter result. In the end, a target detection experiment is given to show the effectiveness of the proposed method using space-air based bistatic radar.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
糖糖关注了科研通微信公众号
刚刚
刚刚
小恶于完成签到 ,获得积分10
刚刚
科研通AI2S应助落晨采纳,获得10
1秒前
1秒前
2秒前
半颗橙子发布了新的文献求助10
2秒前
小可爱完成签到 ,获得积分10
2秒前
3秒前
4秒前
4秒前
Jiangnj发布了新的文献求助30
4秒前
samantha完成签到,获得积分10
5秒前
5秒前
俎树同完成签到 ,获得积分10
5秒前
Natsu完成签到,获得积分10
5秒前
马保国123发布了新的文献求助10
6秒前
丘比特应助无限的隶采纳,获得10
6秒前
在云里爱与歌完成签到,获得积分10
7秒前
迟大猫应助研究生采纳,获得10
7秒前
可行完成签到,获得积分10
7秒前
7秒前
yuhui完成签到,获得积分10
7秒前
8秒前
pi发布了新的文献求助10
8秒前
8秒前
小蘑菇应助科研菜鸟采纳,获得10
9秒前
Owen应助晚风采纳,获得10
9秒前
小二郎应助Jiangnj采纳,获得10
9秒前
微信研友完成签到,获得积分10
9秒前
科研通AI5应助陈杰采纳,获得10
9秒前
10秒前
Jasper应助含糊采纳,获得10
10秒前
dfggg发布了新的文献求助10
10秒前
跑在颖发布了新的文献求助10
10秒前
10秒前
10秒前
10秒前
yatou5651发布了新的文献求助10
10秒前
11秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527742
求助须知:如何正确求助?哪些是违规求助? 3107867
关于积分的说明 9286956
捐赠科研通 2805612
什么是DOI,文献DOI怎么找? 1540026
邀请新用户注册赠送积分活动 716884
科研通“疑难数据库(出版商)”最低求助积分说明 709762