一种面向机械旋转变极化雷达的蝙蝠超分辨改进算法

王博弘; 申彪; 穆文星; 刘涛

doi:10.12000/JR25113

一种面向机械旋转变极化雷达的蝙蝠超分辨改进算法

DOI: 10.12000/JR25113 CSTR: 32380.14.JR25113

海军工程大学武汉 430033

基金项目: 国家自然科学基金(62571542, 62171452)

详细信息

作者简介:
王博弘，硕士生，主要研究方向为雷达超分辨技术、雷达极化信息处理等

申　彪，博士生，主要研究方向为极化雷达波形设计、雷达极化抗干扰和雷达极化信息处理等

穆文星，博士生，主要研究方向为雷达极化信息处理和极化SAR目标检测等

刘　涛，博士，教授，博士生导师，主要研究方向为雷达极化信息处理、新体制雷达技术及雷达电子战等

通讯作者:
刘涛 liutao1018@sina.com

责任主编：高贵 Corresponding Editor: GAO Gui
中图分类号: TN957
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出版历程
- 收稿日期: 2025-06-19
- 修回日期: 2025-08-22
- 网络出版日期: 2025-09-11

An Improved Bat-inspired Super-resolution Algorithm for Mechanical Rotation Polarimetric Radar

Naval University of Engineering, Wuhan 430033, China

Funds: The National Natural Science Foundation of China (62571542, 62171452)

More Information

Corresponding author: LIU Tao, liutao1018@sina.com

摘要

摘要: 近年来，受生物感知机制启发的仿生超分辨技术已成为突破雷达分辨极限的重要研究方向。基于蝙蝠听觉的基带谱相关及变换(BSCT)模型为传统雷达分辨力提升提供了新思路，然而其存在多目标适应能力不足且无法利用极化信息的固有缺陷。针对上述问题，该文提出一种面向机械旋转变极化雷达(MRPR)的极化增强型仿生超分辨模型：极化基带谱相关及变换(P-BSCT)。主要贡献包括：一是将蝙蝠BSCT模型与MRPR结合，使之可以利用极化信息并进行极化测量；二是提出改进的信号处理方法，突破原BSCT对两目标、静态场景的限制，有效适用于多目标及运动目标场景，且分辨效果不受信号调制形式影响。仿真实验表明，在理想条件下，P-BSCT相较原BSCT模型带来约15 dB的分辨力提升；对于运动目标、极化散射特性相同的目标以及非线性调频信号等特殊场景，P-BSCT的分辨性能基本不受影响，具有较强的鲁棒性。
- 仿生超分辨 /
- 基带谱相关及变换(BSCT) /
- 机械旋转变极化雷达(MRPR) /
- 子空间分解 /
- 极化测量
Abstract: In recent years, bionic super-resolution technology, inspired by biological perception mechanisms, has emerged as a substantial research direction aimed at overcoming the limitations of radar resolution. The Baseband Spectrogram Correlation and Transformation (BSCT) model, which is based on bat hearing, offers a novel approach to enhancing traditional radar resolution. However, the model exhibits inherent limitations, including insufficient multi-target adaptability and the inability to utilize polarization information. To address these problems, this paper proposes a polarization-enhanced bionic super-resolution model: Polarimetric Baseband Spectrogram Correlation and Transformation (P-BSCT) for Mechanical Rotation Polarimetric Radar (MRPR). The primary contributions of this study are as follows: first, the integration of the bat BSCT model with MRPR, thereby enabling the utilization of polarization information and the execution of polarization measurements; second, the proposal of an advanced signal processing method, which overcomes the limitations of the original BSCT in two-target and static scenes, effectively applying to multi-target and moving-target scenarios, and exhibiting no impact on the resolution effect due to signal modulation. P-BSCT has been demonstrated to enhance resolving power by approximately 15 dB under optimal conditions when compared with the original BSCT model. In scenarios involving moving targets, targets exhibiting equivalent polarization scattering properties, and nonlinear FM signals, the resolving performance of P-BSCT remains essentially unchanged, demonstrating notable robustness.

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图 1 MRPR系统结构框图与实物图^[74]

Figure 1. Block diagram and physical diagram of the MRPR system structure^[74]

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图 2 P-BSCT信号处理流程图

Figure 2. Flowchart of P-BSCT signal processing

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图 3 两目标条件下不同算法在不同相对距离时的分辨效果

Figure 3. Resolution effects of different algorithms at various relative distances under two-target condition

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图 4 算法分辨力对比

Figure 4. Comparison of resolution among several algorithms

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图 5 无噪声下6种算法对多目标的分辨效果对比

Figure 5. Comparison of multi-target resolution effects of 6 algorithms under no-noise condition

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图 6 无噪声下P-BSCT和Single-snap MUSIC多目标场景的分辨效果对比

Figure 6. Comparison of resolution effects of P-BSCT and Single-snap MUSIC in multi-target scenarios under no-noise condition

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图 7 两目标条件下噪声对4种仿生超分辨算法分辨效果的影响

Figure 7. Influence of noise on resolution effects of 4 bionic super-resolution algorithms under two-target condition

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图 8 多目标场景下噪声对P-BSCT和Single-snap MUSIC分辨效果的影响

Figure 8. Influence of noise on resolution effects of P-BSCT and Single-snap MUSIC in multi-target scenarios

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图 9 相干脉冲数对分辨效果的影响

Figure 9. Influence of coherent pulse number on resolution effect

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图 10 极化测量误差随相干脉冲数变化曲线

Figure 10. Curve of polarization measurement error variation with coherent pulse number

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图 11 探究旋转变极化对分辨效果提升的作用

Figure 11. Investigation on the role of rotating variable polarization in improving resolution effect

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图 12 信号形式对P-BSCT和Single-snap MUSIC分辨效果的影响

Figure 12. Influence of signal forms on resolution effects of P-BSCT and Single-snap MUSIC

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图 13 运动扩展目标下P-BSCT速度估计与超分辨效果

Figure 13. Velocity estimation and super-resolution effect of P-BSCT for moving extended targets

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图 14 目标PSM相同与否对P-BSCT分辨效果的影响

Figure 14. Influence of whether target PSMs are identical or not on resolution effect of P-BSCT

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图 15 目标PSM不同与相同时P-BSCT的极化测量误差随SNR变化曲线

Figure 15. Curves of polarization measurement error of P-BSCT varied with SNR when target PSMs are different or identical

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图 16 信噪比对极化测量误差的影响

Figure 16. Influence of SNR on polarization measurement error

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图 17 分辨单元内P-BSCT的分辨效果与目标个数、目标间距和信噪比的关系

Figure 17. Relationship between resolution effect of P-BSCT in resolution cell and number of targets, target spacing, and SNR

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图 18 极化测量误差随极化角度误差变化曲线

Figure 18. Curve of polarization measurement error variation with polarization angle error

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图 19 极化测量误差随速度估计误差变化曲线

Figure 19. Curve of polarization measurement error variation with velocity estimation error

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表 1 仿真参数设置

Table 1. Simulation parameter settings

参数	数值
载频	600 MHz
带宽	200 MHz
脉宽	2 μs
脉冲重复间隔(PRI)	0.5 ms
天线旋转速度	1666.7 r/min
天线初始角度	0°
脉冲个数	72
耳蜗滤波器组数目	81

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表 2 无噪声下P-BSCT算法对4个目标PSM的测量结果

Table 2. Measurement results of PSM for 4 targets using P-BSCT algorithm under no-noise condition

目标	真实值	测量值	测量误差(%)	平均测量误差(%)
目标1	$\left[ {\begin{array}{*{20}{c}} {1.00 + 0.00{\text{i}}}&{0.00 + 0.00{\text{i}}} \\ {0.00 + 0.00{\text{i}}}&{ - 1.00 + 0.00{\text{i}}} \end{array}} \right]$	$\left[ {\begin{array}{*{20}{c}} {0.99 + 0.14{\text{i}}}&{0.00 + 0.00{\text{i}}} \\ {0.00 + 0.00{\text{i}}}&{ - 0.99 - 0.14{\text{i}}} \end{array}} \right]$	0	2.22
目标2	$\left[ {\begin{array}{*{20}{c}} {0.50 + 0.00{\text{i}}}&{0.00 + 0.50{\text{i}}} \\ {0.00 + 0.50{\text{i}}}&{0.50 + 0.00{\text{i}}} \end{array}} \right]$	$\left[ {\begin{array}{*{20}{c}} {0.51 + 0.06{\text{i}}}&{ - 0.07 + 0.49{\text{i}}} \\ { - 0.07 + 0.49{\text{i}}}&{0.50 + 0.08{\text{i}}} \end{array}} \right]$	3.56
目标3	$\left[ {\begin{array}{*{20}{c}} {0.75 + 0.00{\text{i}}}&{0.43 + 0.00{\text{i}}} \\ {0.43 + 0.00{\text{i}}}&{0.25 + 0.00{\text{i}}} \end{array}} \right]$	$\left[ {\begin{array}{*{20}{c}} {0.76 - 0.10{\text{i}}}&{0.42 - 0.06{\text{i}}} \\ {0.42 - 0.06{\text{i}}}&{0.25 - 0.02{\text{i}}} \end{array}} \right]$	2.54
目标4	$\left[ {\begin{array}{*{20}{c}} {1.00 + 0.00{\text{i}}}&{0.15 + 0.00{\text{i}}} \\ {0.15 + 0.00{\text{i}}}&{0.73 + 0.53{\text{i}}} \end{array}} \right]$	$\left[ {\begin{array}{*{20}{c}} {1.00 - 0.14{\text{i}}}&{0.14 - 0.02{\text{i}}} \\ {0.14 - 0.02{\text{i}}}&{0.80 + 0.43{\text{i}}} \end{array}} \right]$	0.78

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表 3 无噪声下Single-snap MUSIC算法对4个目标PSM的测量结果

Table 3. Measurement results of PSM for 4 targets using Single-snap MUSIC algorithm under no-noise condition

目标	真实值	测量值	测量误差(%)	平均测量误差(%)
目标1	$\left[ {\begin{array}{*{20}{c}} {1.00 + 0.00{\text{i}}}&{0.00 + 0.00{\text{i}}} \\ {0.00 + 0.00{\text{i}}}&{ - 1.00 + 0.00{\text{i}}} \end{array}} \right]$	$\left[ {\begin{array}{*{20}{c}} {1.00 + 0.00{\text{i}}}&{0.01 - 0.00{\text{i}}} \\ {0.01 - 0.00{\text{i}}}&{ - 0.99 - 0.02{\text{i}}} \end{array}} \right]$	1.73	4.13
目标2	$\left[ {\begin{array}{*{20}{c}} {0.50 + 0.00{\text{i}}}&{0.00 + 0.50{\text{i}}} \\ {0.00 + 0.50{\text{i}}}&{0.50 + 0.00{\text{i}}} \end{array}} \right]$	$\left[ {\begin{array}{*{20}{c}} {0.50 + 0.00{\text{i}}}&{ - 0.01 + 0.48{\text{i}}} \\ { - 0.01 + 0.48{\text{i}}}&{0.49 - 0.01{\text{i}}} \end{array}} \right]$	3.06
目标3	$\left[ {\begin{array}{*{20}{c}} {0.75 + 0.00{\text{i}}}&{0.43 + 0.00{\text{i}}} \\ {0.43 + 0.00{\text{i}}}&{0.25 + 0.00{\text{i}}} \end{array}} \right]$	$\left[ {\begin{array}{*{20}{c}} {0.75 + 0.00{\text{i}}}&{0.47 + 0.02{\text{i}}} \\ {0.47 + 0.02{\text{i}}}&{0.27 - 0.05{\text{i}}} \end{array}} \right]$	7.58
目标4	$\left[ {\begin{array}{*{20}{c}} {1.00 + 0.00{\text{i}}}&{0.15 + 0.00{\text{i}}} \\ {0.15 + 0.00{\text{i}}}&{0.73 + 0.53{\text{i}}} \end{array}} \right]$	$\left[ {\begin{array}{*{20}{c}} {1.00 + 0.00{\text{i}}}&{0.13 + 0.01{\text{i}}} \\ {0.13 + 0.01{\text{i}}}&{0.78 + 0.53{\text{i}}} \end{array}} \right]$	4.17

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表 4 运动扩展目标下P-BSCT算法对4个目标PSM的测量结果

Table 4. Measurement results of PSM for 4 targets using P-BSCT algorithm under moving extended targets condition

目标	真实值	测量值	测量误差(%)	平均测量误差(%)
目标1	$\left[ {\begin{array}{*{20}{c}} {1.00 + 0.00{\text{i}}}&{0.00 + 0.00{\text{i}}} \\ {0.00 + 0.00{\text{i}}}&{ - 1.00 + 0.00{\text{i}}} \end{array}} \right]$	$\left[ {\begin{array}{*{20}{c}} {0.98 - 0.10{\text{i}}}&{0.00 - 0.00{\text{i}}} \\ {0.00 - 0.00{\text{i}}}&{ - 0.99 + 0.10{\text{i}}} \end{array}} \right]$	0.72	0.81
目标2	$\left[ {\begin{array}{*{20}{c}} {0.50 + 0.00{\text{i}}}&{0.00 + 0.50{\text{i}}} \\ {0.00 + 0.50{\text{i}}}&{0.50 + 0.00{\text{i}}} \end{array}} \right]$	$\left[ {\begin{array}{*{20}{c}} {0.49 - 0.06{\text{i}}}&{0.05 + 0.49{\text{i}}} \\ {0.05 + 0.49{\text{i}}}&{0.50 - 0.06{\text{i}}} \end{array}} \right]$	1.65
目标3	$\left[ {\begin{array}{*{20}{c}} {0.75 + 0.00{\text{i}}}&{0.43 + 0.00{\text{i}}} \\ {0.43 + 0.00{\text{i}}}&{0.25 + 0.00{\text{i}}} \end{array}} \right]$	$\left[ {\begin{array}{*{20}{c}} {0.73 + 0.09{\text{i}}}&{0.42 + 0.05{\text{i}}} \\ {0.42 + 0.05{\text{i}}}&{0.24 + 0.03{\text{i}}} \end{array}} \right]$	0.47
目标4	$\left[ {\begin{array}{*{20}{c}} {1.00 + 0.00{\text{i}}}&{0.15 + 0.00{\text{i}}} \\ {0.15 + 0.00{\text{i}}}&{0.73 + 0.53{\text{i}}} \end{array}} \right]$	$\left[ {\begin{array}{*{20}{c}} {0.98 + 0.12{\text{i}}}&{0.15 + 0.02{\text{i}}} \\ {0.15 + 0.02{\text{i}}}&{0.65 + 0.61{\text{i}}} \end{array}} \right]$	0.41

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表 5 分辨单元内P-BSCT的分辨力与SNR和目标个数的关系

Table 5. Relationship between resolution of P-BSCT in a resolution cell and SNR, number of targets

目标个数	SNR (dB)
目标个数	–20	–10	0	10	20	30	40
2	0.85	0.37	0.18	0.06	0.04	0.03	0.03
3	\	\	0.44	0.39	0.36	0.18	0.16
4	\	\	\	\	0.31	0.29	0.20
5	\	\	\	\	\	0.22	0.16
注：表格中数据为归一化分辨力：分辨力(m)/瑞利分辨力(m)。斜线表示：在分辨单元内的目标个数和SNR满足当前条件下，无论目标间隔多大，都无法稳健分辨。

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表 6 4种仿生超分辨方法性能对比

Table 6. Performance comparison of four bionic super-resolution methods

信号处理方法	分辨力(m) / 瑞利分辨力(m)	是否适用于多目标场景	抗噪声能力
匹配滤波	≈1.4	是	强
基向量解卷积	≈0.5	否	中
BSCT	≈0.9	否	中
改进BSCT	≈0.6	否	弱
P-BSCT (谱峰搜索法)	≈0.03	是	强
P-BSCT (直接计算法)	<0.03	是	较强

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表 7 P-BSCT与Single-snap MUSIC性能对比

Table 7. Performance comparison between P-BSCT and Single-snap MUSIC

评价项目	P-BSCT	Single-snap MUSIC
抗噪声性能	较强	弱
分辨与极化测量精度	较高	较低
是否依赖信号形式	否	是
是否适用于运动目标	是	否

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