The marginal Fisher information (MFI) metric is used to design waveforms for the sake of informationally optimal adaptive-on-transmit radar operation. A framework for MFI waveform design is developed and the Polyphase-Coded FM (PCFM) waveform model is utilised to produce a constant-modulus, spectrally contained signal amenable to transmission with high-power amplifiers. The efficacy of the MFI waveform design and minimum mean square error (MMSE) estimation is experimentally demonstrated and extended into an adaptive and dynamic sensing paradigm. The radar transmit waveform is optimised to maximise the Fisher information with respect to the range profile. Upon observing new information from radar echoes, the iterative MMSE (iMMSE) estimator then minimises the estimation error variance according to prior observations. Sequential information maximisation (via waveform design) and error minimisation (via iMMSE) tends towards the Cramér–Rao lower bound (CRLB) with additional measurements improving radar resolution and accuracy. These concepts maximise the information extracted by a radar operating in a congested spectrum where the available bandwidth is limited.

中文翻译：

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信息论波形设计及其在自适应发射雷达中的应用

边际费希尔信息 (MFI) 度量用于设计波形，以实现信息最优的自适应发射雷达操作。开发了 MFI 波形设计框架，并利用多相编码 FM (PCFM) 波形模型来生成适合用高功率放大器传输的恒模、频谱包含信号。 MFI 波形设计和最小均方误差 (MMSE) 估计的功效经过实验证明，并扩展到自适应动态传感范例。雷达发射波形经过优化，可最大化有关距离剖面的费希尔信息。在从雷达回波中观察到新信息后，迭代 MMSE (iMMSE) 估计器会根据先前的观察结果最小化估计误差方差。顺序信息最大化（通过波形设计）和误差最小化（通过 iMMSE）趋向于 Cramér–Rao 下限 (CRLB)，并通过附加测量提高雷达分辨率和精度。这些概念最大限度地提高了在可用带宽有限的拥挤频谱中运行的雷达提取的信息。