基于基带S模式信号的联合TOA估计算法研究

Research on joint TOA estimation algorithm based on baseband mode S signal

  • 摘要: 针对广域多点定位系统中接收信号信噪比(signal to noise ratio, SNR)低导致到达时间(time of arrival, TOA)提取不准确的问题,提出了一种匹配滤波结合非相干积累的联合TOA估计算法,该算法能够有效降低匹配滤波法在低SNR下TOA估计的均方根误差(root mean square error, RMSE). 联合算法通过对二次雷达驻留时间内接收的应答信号的匹配滤波输出做非相干积累,在最大值点处标记时间戳进行TOA估计,利用能量累积原理提高SNR,从而使得估计精确度得以提升. 仿真结果表明:该算法可在−15 dB SNR,53 MHz采样频率及9个积累信号时,达到24.302 ns的TOA估计精确度. 所提联合TOA估计算法具有高精确度与高稳健性的特点,能够在−15~0 dB SNR 将估计精确度提升至25 ns以下,为提取低SNR S模式信号TOA进而提升广域多点定位精确度提供了一种有效的方法.

     

    Abstract: Aiming at the problem of inaccurate time of arrival (TOA) extraction caused by low signal-to-noise ratio (SNR) of received signals in wide area multilateration system, a joint TOA estimation algorithm combining matched filter and non-coherent integration is proposed, which can effectively reduce the root mean square error (RMSE) of the matched filter TOA estimation method under low SNR. The joint algorithm does the non-coherent integration of the matched filter output of the received reply signals within the dwell time of the secondary surveillance radar, marks a time stamp at the maximum point for TOA estimation, and uses the principle of energy accumulation to improve the SNR, so as to improve the estimation accuracy. The simulation results show that the algorithm can achieve a TOA estimation accuracy of 24.302 ns at −15 dB SNR, 53 MHz sampling frequency and 9 accumulated signals. The proposed joint TOA estimation algorithm has the characteristics of high accuracy and high robustness, and can improve the estimation accuracy to less than 25 ns at the SNR of −15 dB to 0 dB. It provides an effective method for extracting the TOA of mode S signals with low SNR and improving the positioning accuracy of wide area multilateration.

     

/

返回文章
返回