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Transceiver Design for an FDA-MIMO Radar and MIMO Communication Spectral Coexistence System
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摘要: 雷达与通信在一个平台占用相同频谱时会产生相互干扰，此外雷达目标探测过程中面临主瓣方向的欺骗式干扰威胁。为解决上述问题，该文设计了一种频率分集阵多输入多输出(FDA-MIMO)雷达和MIMO通信频谱共存系统，提出了一种雷达为中心的系统收发参数联合设计方法。该方法通过联合优化雷达发射波形、雷达接收滤波器和通信发射码本，最大化雷达系统的输出信干噪比(SINR)，从而提高对目标的检测概率，同时保证MIMO通信速率。在优化过程中，采用交替优化(AO)策略，将优化问题分解为多个子问题并迭代求解。其中，接收滤波器的优化通过拉格朗日乘子法求解，通信发射码本优化采用不等式定理得到最优近似解，而雷达发射波形优化通过泰勒展开和松弛算法进行凸近似。仿真结果表明，该联合设计方法能够在保证通信速率的同时有效提高雷达系统的SINR，显著提升FDA-MIMO雷达和MIMO通信频谱共存系统在主瓣欺骗式干扰下的性能。
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关键词:
- 雷达通信频谱共存 /
- 频率分集阵多输入多输出 /
- 收发联合设计 /
- 交替优化 /
- 主瓣欺骗式干扰抑制
Abstract: When radar and communication systems share the same frequency spectrum on the same platform, mutual interference may occur. In addition, mainlobe deceptive interferences pose a serious threat to radar target detection. To address these issues, we devise a Frequency Diverse Array Multiple-Input Multiple-Output (FDA-MIMO) radar and MIMO communication spectral coexistence system and propose a radar-centric joint transceiver design scheme. In this respect, the radar transmission waveform, radar receive filter, and communication transmission codebook are optimized to maximize the Signal-to-Interference-plus-Noise Ratio (SINR) of the radar system, thereby enhancing the target detection probability while ensuring MIMO communication throughput. During the optimization process, the Alternating Optimization (AO) strategy is employed to decompose the problem into multiple subproblems, which are solved in an iterative way. Specifically, the radar receive filter is obtained using the Lagrange multiplier method. In addition, the communication transmission codebook is approximated using an inequality theorem, and the radar transmission waveform is optimized using Taylor expansion and relaxation algorithms. Simulation results reveal that this joint design method can effectively improve the SINR of the radar system while ensuring communication throughput, thereby considerably enhancing the performance of the FDA-MIMO radar and MIMO communication spectral coexistence system under mainlobe jamming conditions. -
图 1 FDA-MIMO雷达和MIMO通信频谱共存系统模型
Figure 1. FDA-MIMO radar and MIMO communication spectral coexistence system model
图 2 联合优化后SINR随着迭代次数的变化曲线
Figure 2. SINR convergence with iteration number after joint optimization
图 3 不同$\xi $条件SINR随着迭代次数的变化曲线
Figure 3. SINR convergence with iteration number under varying parameter $\xi $
图 4 算法优化后方向图对比
Figure 4. Comparison of beampattern performance through algorithm optimization
1 基于AO的FDA-MIMO雷达和MIMO通信频谱共存系统收发联合优化算法
1. Transceiver design for FDA-MIMO radar and MIMO communication spectral coexistence system based on AO strategy
输入：${C_{\mathrm{t}}}$, ${E_{\mathrm{t}}}$, $\xi $, $\varsigma $ 初始化：$n = 0$, $ {\boldsymbol{R}}_{\text{x}}^{\left( {0} \right)} = \left( {{E_{\text{t}}}/(L{N_{\text{t}})}} \right){{\boldsymbol{I}}_{{N_{\text{t}}}L}} $, ${{\boldsymbol{s}}^{\left( 0 \right)}}$, ${{\boldsymbol{w}}^{\left( 0 \right)}}$ repeat 1.$n = n + 1$ 2.根据式(25)计算接收滤波器${{\boldsymbol{w}}^{\left( n \right)}}$ 3.使用MATLAB中的linprog函数求解问题式(34)得到通信码本
$ {\boldsymbol{R}}_{\text{x}}^{\left( n \right)} $4.使用MATLAB中的CVX工具箱求解问题式(44)，再利用秩1近
似法得到雷达波形${{\boldsymbol{s}}^{\left( n \right)}}$5.计算当前${\text{SIN}}{{\text{R}}^{\left( n \right)}}$ until $\left| {{\text{SIN}}{{\text{R}}^{\left( n \right)}} - {\text{SIN}}{{\text{R}}^{\left( {n - 1} \right)}}} \right| < \varsigma $ 输出：${{\boldsymbol{w}}_{{\text{opt}}}} = {{\boldsymbol{w}}^{\left( n \right)}}$, ${{\boldsymbol{s}}_{{\text{opt}}}} = {{\boldsymbol{s}}^{\left( n \right)}}$, ${{\boldsymbol{R}}_{\text{x}}}_{{\text{opt}}} = {\boldsymbol{R}}_{\text{x}}^{\left( n \right)}$,
${\text{SIN}}{{\text{R}}_{{\text{opt}}}} = {\text{SIN}}{{\text{R}}^{\left( n \right)}}$
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表 1 FDA-MIMO雷达和MIMO通信频谱共存系统参数表
Table 1. FDA-MIMO radar and MIMO communication spectral coexistence system simulation parameters
参数 取值 参数 取值 载频$ {f_0} $ 1 GHz ${{\boldsymbol{H}}_{{\text{CR}}}}$路径数${P_1}$ 15 频偏$\Delta f$ 3000 Hz${{\boldsymbol{H}}_{{\text{RC}}}}$路径数${P_2}$ 15 码长L 6 目标信噪比 10 dB
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