基于空域特性的低空空域雷达目标检测
收稿日期: 2014-08-26
修回日期: 2014-11-24
网络出版日期: 2014-12-01
基金资助
民航安全能力建设资金(142146903072)
Radar target detection in low-altitude airspace with spatial features
Received date: 2014-08-26
Revised date: 2014-11-24
Online published: 2014-12-01
Supported by
Safety Capability Construction Funds of Civil Aviation (142146903072)
为实现基于非相参雷达的低空空域监视,提出一种基于空域特性的杂波抑制算法,通过构造"最优分类面"来区分复杂低空空域雷达图像中的小弱目标和杂波,极大改善了非相参雷达的低空探测能力。首先,采用背景差分与固定阈值分割建立前景和背景统计模型。然后,基于该模型提取空域特性,建立马尔可夫随机场模型,从而自适应地调节"最优分类面"中的阈值。前景模型数据反映了待检测像素的聚集程度,背景模型数据反映了其相对位置。将本算法分别应用于X波段和S波段航海雷达获取的图像序列。检测结果表明:本算法在检测到低空空域小弱目标的同时,能够将虚警率保持在较低的水平,优于恒虚警检测等经典算法。最后,将本算法与已经实现的目标跟踪算法相结合,实现了一整套完整的低空空域雷达目标检测与跟踪算法。
陈唯实 , 李敬 . 基于空域特性的低空空域雷达目标检测[J]. 航空学报, 2015 , 36(9) : 3060 -3068 . DOI: 10.7527/S1000-6893.2014.0324
To achieve the surveillance of low-altitude airspace with the incoherent radar, a clutter suppression algorithm was proposed based on the spatial features with the purpose of distinguishing the dim small targets from clutters in the radar images of complex low-altitude airspace by the construction of an optimal classification plane, greatly improving the detection capability of the incoherent radar in low-altitude airspace. Firstly, the foreground and background statistical models are built by background subtraction and fixed threshold method. Then, with the spatial features extracted from these models, a Markov random field model is established to adapt to the thresholds in the optimal classification plane. The statistics from the foreground model reflected the aggregation degree of the concerned pixels, while those from the background model reflected their relative positions. The proposed algorithm is applied to the image sequences obtained with X-band and S-band marine radars. The detection results demonstrate that the proposed algorithm could detect the dim small targets with relatively low false alarm rate, outperforming the classical algorithms such as the constant false alarm rate. Finally, the proposed algorithm is combined with the target tracking algorithm achieved in the previous research, therefore an advanced algorithm is provided for the detection and tracking of radar targets in complex low-altitude airspace.
Key words： low-altitude airspace; radar; target; detection; optimal classification plane
[1] Yang Y, Sui D. Thoughts on reforming low altitude airspace and development of general aviation in China[J]. Journal of Nanjing University of Aeronautics and Astronautics: Social Sciences, 2010, 12(2): 50-53 (in Chinese). 杨勇, 隋东. 我国低空空域改革和通用航空事业发展有关问题的思考[J]. 南京航空航天大学学报: 社会科学版, 2010, 12(2): 50-53.
[2] Lv M H, Yu Q Y, Zhou Q, et al. Applications of new ATM technology in low altitude space management[J]. Communications Technology, 2009, 42(12): 95-100 (in Chinese). 吕茂辉, 余秦勇, 周琦, 等. 空管新技术在低空空域管理中的应用[J]. 通信技术, 2009, 42(12): 95-100.
[3] Zhang J. New development and application of airspace surveillance technology[J]. Acta Aeronautica et Astronautica Sinica, 2011, 32(1): 1-14 (in Chinese). 张军. 空域监视技术的新进展及应用[J]. 航空学报, 2011, 32(1): 1-14.
[4] Wang X M, Kuang Y S, Chen Z X. Surveillance radar technology[M]. Beijing: Publishing House of Electronics Industry, 2008: 167-169 (in Chinese). 王小谟, 匡永胜, 陈忠先. 监视雷达技术[M]. 北京: 电子工业出版社, 2008: 167-169.
[5] Anderson R. Technical data sheet of HARRIER security radars for airspace surveillance[EB/OL]. (2011-05-26) [2014-08-30]. http://www.detect-inc.com/downloads.
[6] Nohara T J, Weber P, Jones G, et al. Affordable high-performance radar networks for homeland security applications[C]//IEEE Radar Conference. Piscataway, NJ: IEEEPress, 2008: 1-6.
[7] Merrill I S. Radar handbook[M]. 3rd ed. New York: The McGraw-Hill Companies Inc., 2008: 401-402.
[8] He Y, Xiu J J, Zhang J W, et al. Radar data processing with applications[M]. 2nd ed. Beijing: Publishing House of Electronics Industry, 2009: 2-6 (in Chinese). 何友, 修建娟, 张晶炜, 等. 雷达数据处理及应用[M]. 2版. 北京: 电子工业出版社, 2009: 2-6.
[9] Wu S J, Mei X C. Radar signal processing and data processing technology[M]. Beijing: Publishing House of Electronics Industry, 2008: 406-417 (in Chinese). 吴顺君, 梅晓春. 雷达信号处理和数据处理技术[M]. 北京: 电子工业出版社, 2008: 406-417.
[10] Chen W S, Ning H S. Security surveillance of low-altitude airspace with primary radar[J]. Journal of Beijing University of Aeronautics and Astronautics, 2012, 38(2): 143-148 (in Chinese). 陈唯实, 宁焕生. 利用一次雷达实现低空空域的安全监视[J]. 北京航空航天大学学报, 2012, 38(2): 143-148.
[11] McHugh J M, Konrad J, Saligrama V, et al. Foreground-adaptive background subtraction[J]. IEEE Signal Processing Letters, 2009, 16(5): 390-393.
[12] Richards M A. Fundamentals of radar signal processing[M]. New York: McGraw-Hill, 2005: 1-5.
[13] Rohling H. Radar CFAR thresholding in clutter and multiple target situations[J]. IEEE Transactions on Aerospace and Electronic Systems, 1983, 19(4): 608-621.
[14] Laroussi T, Barkat M. Performance analysis of order-statistic CFAR detectors in time diversity systems for partially correlated chi-square targets and multiple target situations: A comparison[J]. Signal Processing, 2006, 86(7): 1617-1631.
[15] Han D S. Detection performance of CFAR detectors based on order statistics for partially correlated chi-square targets[J]. IEEE Transactions on Aerospace and Electronic Systems, 2000, 36(4): 1423-1429.
[16] Guida M, Longo M, Lops M. Biparametric CFAR procedures for lognormal clutter[J]. IEEE Transactions on Aerospace and Electronic Systems, 1993, 29(3): 798-809.
[17] El Mashade M B. Monopulse detection analysis of the trimmed mean CFAR processor in nonhomogeneous situations[J]. IEE Proceedings: Radar Sonar and Navigation, 1996, 143(2): 87-94.
[18] Biao C, Varshney P K, Michels J H. Adaptive CFAR detection for clutter-edge heterogeneity using Bayesian inference[J]. IEEE Transactions on Aerospace and Electronic Systems, 2003, 39(4): 1462-1470.
[19] Smith M E, Varshney P K. Intelligent CFAR processor based on data variability[J]. IEEE Transactions on Aerospace and Electronic Systems, 2000, 36(3): 837-847.
[20] Guan J, He Y. Performance analysis of OSCAGO-CFAR detector under clutter edge situation[J]. Acta Electronica Sinica, 1996, 24(3): 56-60 (in Chinese). 关键, 何友. OSCAGO-CFAR检测器在干扰边缘中的性能分析[J]. 电子学报, 1996, 24(3): 56-60.
[21] Sun P F, Huang Y, Bao Z H, et al. An algorithm to improve navigation radar display effect after CFAR detection[J]. Radar Science and Technology, 2013, 11(5): 5-8 (in Chinese). 孙鹏飞, 黄勇, 包中华, 等. 一种改善导航雷达恒虚警检测效果的算法[J]. 雷达科学与技术, 2013, 11(5): 5-8.
[22] Chen J J, Huang M J, Qiu W, et al. A novel method for CFAR detector with bi-thresholds in sea clutter[J]. Acta Electronica Sinica, 2011, 39(9): 2135-2141 (in Chinese). 陈建军, 黄孟俊, 邱伟, 等. 海杂波下的双门限恒虚警目标检测新方法[J]. 电子学报, 2011, 39(9): 2135-2141.
[23] Sui T Y, Xiao F, Zhang L, et al. Double-decision frame synchronization algorithm based on constant false alarm variable[J]. Communications Technology, 2014, 47(9): 994-998 (in Chinese). 隋天宇, 肖飞, 张雷, 等. 一种基于恒虚警检测量的双判决帧同步方法[J]. 通信技术, 2014, 47(9): 994-998.
[24] Vicen-Bueno R, Carrasco-Alvarez R, Jarabo-Amores M P, et al. Ship detection by different data selection templates and multilayer perceptrons from incoherent maritime radar data[J]. IET Radar, Sonar and Navigation, 2011, 5(2): 144-154.
[25] Wang X Z, Liu Y. Application of wavelet and morphology in the processing of radar PPI clutter & noise[J]. Electronics Optics & Control, 2003, 10(1): 47-49 (in Chinese). 王新智, 刘雨. 小波和形态学在雷达平面位置图像杂噪处理中的应用[J]. 电光与控制, 2003, 10(1): 47-49.
[26] Ning H S, Chen W S, Li J. Radar target tracking in cluttered environment based on particle filtering[J]. The Aeronautical Journal, 2010, 114(1155): 309-314.
/
| 〈 |
|
〉 |
CJA