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摘要: 相比于单部雷达系统，空间分置的网络化雷达由于空间分集、频率分集等优势，通常具备更优的探测性能。当前基于网络化雷达系统的融合检测方法大多仅依据目标回波幅度信息，未考虑相参雷达系统能够获取的多普勒信息对融合检测的增益。直观地，网络化雷达系统中不同雷达观测到目标的空间位置与径向速度应当满足一定的物理约束，利用该额外信息应当能够提升目标与虚警的可分性。基于此，该文提出了多普勒信息辅助的网络化雷达融合检测算法：首先利用多雷达站对同一目标角度与多普勒速度观测的耦合性构建观测间需要满足的约束不等式组，然后基于运筹学中两阶段法对该不等式组是否有可行解做出判断，进而对目标是否存在做出判决。仿真实验表明，所提算法能够有效提升网络化雷达系统的融合检测性能。同时，该文还针对所提算法分析了雷达布站位置及目标位置对融合检测性能的影响。Abstract: Compared with single-radar systems, spatially separated networked radar usually has better detection performance due to its advantages of spatial and frequency diversities. Most of the current fusion detection methods based on networked radar systems only rely on the echo amplitude information of the target without considering the Doppler information that a coherent radar system can obtain to assist detection of targets. Intuitively, the spatial position and radial velocity of a target observed by different radar devices in the networked radar systems should meet certain physical constraints under which the target and false target can be substantially distinguished. Based on this consideration, fusion detection for the networked radar aided by a Doppler information algorithm is proposed in this paper. First, a set of inequalities is constructed based on the coupling between the observation of the same target’s azimuth and Doppler velocity by multiple radar stations. Then, a two-phase method, an algorithm in operational research, is used to judge whether the inequalities have a feasible solution, based on which a judgment is made on whether the target exists. Finally, some simulations are conducted, which show that the proposed algorithm can effectively improve the detection performance of the networked radar system fusion detection. Additionally, the influence of radar station location and target position on the fusion detection performance of the proposed algorithm is analyzed.
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Key words:
- Networked radar /
- Fusion detection /
- Doppler information /
- Two-phase method
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图 2 单雷达站线性不等式组中直线位置关系
Figure 2. Position relation between lines in linear inequalities based on single radar station
图 3 单雷达站对应可行域
${R_i}$ Figure 3. Corresponding feasible region
${R_i}$ of single radar station
图 7 单雷达站对应可行域
${R_i}$ Figure 7. Corresponding feasible region
${R_i}$ of single radar station
图 11 各种传统融合检测器引入多普勒信息辅助检测前后的检测性能
Figure 11. Detection performance of various traditional fusion detectors before and after the introduction of Doppler information
图 15 不同雷达站个数下算法的检测性能曲线
Figure 15. Detection performance of different algorithms applied for scenes with different number of radar stations
图 16 3个雷达站顶角不同时对应的各雷达站位置
Figure 16. Locations of 3 radar stations with different top angles
图 17 不同雷达布站位置下
$\{ {R_i}\} _{i = 1}^3$ 的分布图Figure 17. Distribution of
$\{ {R_i}\} _{i = 1}^3$ based on radar systems with different locations of radars
图 18 不同雷达布站位置下检测性能曲线
Figure 18. Detection performance of algorithm applied in radar systems with different distributions of radars
图 20 不同目标位置下
$\{ {R_i}\} _{i = 1}^3$ 的分布图Figure 20. Distribution of
$\{ {R_i}\} _{i = 1}^3$ based on radar systems with different locations of the target
图 21 不同目标位置下检测性能曲线
Figure 21. Detection performance of algorithm applied in radar systems with different locations of targets
算法 1 多普勒信息辅助的融合检测算法 Alg. 1 Procedures of the proposed fusion detection method 步骤1 利用传统融合检测算法获得初次融合检测结果，若判决
结果为目标不存在则结束算法流程，返回该判决结果；若判决目
标存在则进入步骤2；步骤2 将各雷达站观测到目标的角度${\theta _{{\rm{O}}i} }$和径向多普勒速度${v_{{\rm{O}}i} }$
代入式(13)、式(14)中获得各雷达站对应的两个子线性不等式
组，之后依次选取每雷达站对应的其一子线性不等式组以及遍历
可能的速度模糊数构成一个新的线性不等式组
${\rm{LI} }({q_1},\:{q_2}, \cdots ,\:{q_N},\:{k_1},\:{k_2}, \cdots ,\:{k_N})$；步骤3 对构造的线性不等式组进行遍历，依次利用两阶段算法
对其进行有无可行解的判决，若某个线性不等式组存在可行域，
结束算法流程，返回目标存在的判决，否则转入步骤4；步骤4 对基于幅度信息初次融合检测结果进行修正，返回目标
不存在的判决，算法终止。
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表 1 仿真实验雷达系统主要参数
Table 1. Main parameters of the radar systems in the simulation
参数 数值 载频${f_{\rm{c}}}$ 2 GHz 带宽B 2 MHz 脉冲重复频率${f_{\rm{r}}}$ 3 kHz 相参积累脉冲数${N_{\rm{c}}}$ $32$ 3 dB波束宽度${\theta _{3\;{\rm{dB}}} }$ 2°
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