低信噪比S模式基带信号到达时间估计联合算法

宫峰勋; 第五瑶光

doi:10.13700/j.bh.1001-5965.2023.0027

低信噪比S模式基带信号到达时间估计联合算法

doi: 10.13700/j.bh.1001-5965.2023.0027

宫峰勋^,,
第五瑶光

中国民航大学电子信息与自动化学院，天津 300300

基金项目: 国家重点研发计划(2018YFC0809500)

详细信息

通讯作者:
E-mail：fxgong@cauc.edu.cn

中图分类号: TN911
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出版历程
- 收稿日期: 2023-01-17
- 录用日期: 2023-07-28
- 网络出版日期: 2023-09-04
- 整期出版日期: 2025-02-28

Joint algorithm for time of arrival estimation of S-mode baseband signals with low SNR

GONG Fengxun^,,
DIWU Yaoguang

College of Electronic Information and Automation，Civil Aviation University of China，Tianjin 300300，China

Funds: National Key Research and Development Program of China (2018YFC0809500)

More Information

Corresponding author: E-mail：fxgong@cauc.edu.cn

摘要

摘要:
为提高接收低信噪比(SNR) S模式基带信号时广域多点定位(WAM)精确度，提出基于非相干积累的到达时间(TOA)估计联合算法。依托二次监视雷达(SSR)波束扫描驻留时间内目标应答信号具有的相关特性，提出并建立前导四脉冲匹配滤波、非相干积累的低信噪比基带脉冲信号上升沿估计方法，有效提升−15～5 dB范围低信噪比S模式基带信号TOA估计精确度。蒙特卡罗仿真结果显示，在−15～5 dB范围内的低信噪比S模式基带信号通过联合算法估计TOA的均方根误差(RMSE)优于25 ns。对于非理想S模式基带脉冲信号，信噪比低至−15 dB时，经过5个脉冲非相干积累的联合算法的TOA估计精确度达到22.245 ns，远优于WAM要求。
- 到达时间估计 /
- 低信噪比 /
- 匹配滤波器 /
- 非相干积累 /
- 广域多点定位
Abstract:
To improve the wide area multilateration (WAM) accuracy when receiving S-mode baseband signals with low signal-to-noise ratio (SNR), a joint time of arrival (TOA) estimation algorithm based on non-coherent integration was proposed.According to the correlation characteristics of target reply signals during the beam scanning dwell time of the secondary surveillance radar (SSR), a low SNR baseband pulse signal rising edge estimation method with a four-pulse matched filter and amplitude squared operation and accumulation was proposed, which effectively improved the TOA estimation accuracy of S-mode baseband signals with a low SNR ranging from −15 dB to 5 dB. The Monte Carlo simulation results show that the root mean square error (RMSE) of TOA estimation by using the joint algorithm is less than 25 ns for S-mode signals with a low SNR ranging from −15 dB to 5 dB. For non-ideal S-mode baseband signals, when the SNR is as low as −15 dB, the TOA estimation accuracy of the joint algorithm after the non-coherent integration of five pulses can reach 22.245 ns, which is much better than the WAM requirement.
- time of arrival estimation /
- low signal-to-noise ratio /
- matched filter /
- non-coherent integration /
- wide area multilateration

HTML全文

图 1 S模式应答信号脉冲串

Figure 1. S-mode reply signal pulse string

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图 2 匹配滤波法TOA估计精确度

Figure 2. TOA estimation accuracy of matched filter

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图 3 $ {P_{QY}} $与基带信号信噪比的关系

Figure 3. Relationship between $ {P_{QY}} $ and SNR of baseband signal

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图 4 $ {P_{JQ}} $与累加信号数目${N_{{\text{ncoh}}}}$的关系

Figure 4. Relationship between $ {P_{JQ}} $ and accumulated signal number ${N_{{\text{ncoh}}}}$

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图 5 TOA估计联合算法流程框图

Figure 5. Flow chart of TOA estimation joint algorithm

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图 6 多个理想前导四脉冲信号匹配滤波非相干积累后的TOA估计精确度

Figure 6. TOA estimation accuracy of multiple ideal leading four-pulse signals after matched filter and non-coherent integration

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图 7 多个理想前导单脉冲信号匹配滤波非相干积累后的TOA估计精确度

Figure 7. TOA estimation accuracy of multiple ideal leading single-pulse signals after matched filter and non-coherent integration

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图 8 多个理想前导双脉冲信号匹配滤波非相干积累后的TOA估计精确度

Figure 8. TOA estimation accuracy of multiple ideal leading double-pulse signals aftermatched filter and non-coherent integration

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图 9 多个非理想前导四脉冲信号匹配滤波非相干积累后的TOA估计精确度

Figure 9. TOA estimation accuracy of multiple non-ideal leading four-pulse signals after matched filter and non-coherent integration

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图 10 联合算法所需最少积累信号数目

Figure 10. Minimum number of accumulated signals required for joint algorithm

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表 1 −15 dB时达到25 ns以下估计精度所需运行时间

Table 1. Required operating time to achieve estimation accuracy below 25 ns at −15 dB

采样频率/MHz	最少积累信号数目		RMSE/ns		运行时间/µs
采样频率/MHz	理想前导四脉冲信号	非理想前导四脉冲信号	理想前导四脉冲信号	非理想前导四脉冲信号	理想前导四脉冲信号	非理想前导四脉冲信号
40	8	13	24.475	24.140	190.0	277.0
53	6	9	23.640	24.811	232.0	363.9
80	4	6	23.433	23.563	228.1	333.1
100	3	5	24.182	22.245	211.3	241.2

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