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Waveform Design and DoA-DoD Estimation of OFDM-LFM Signal Based on SDFnT for MIMO Radar

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In comparison to orthogonal frequency division multiplexing (OFDM), the OFDM linear frequency modulation (OFDM-LFM) signal has similar time-bandwidth product, lower peak-to-average power ratio, and higher sensitivity to Doppler frequency shift,… Click to show full abstract

In comparison to orthogonal frequency division multiplexing (OFDM), the OFDM linear frequency modulation (OFDM-LFM) signal has similar time-bandwidth product, lower peak-to-average power ratio, and higher sensitivity to Doppler frequency shift, making it a promising candidate waveform for multiple-in multiple-out (MIMO) radar applications. However, the OFDM-LFM signal is unsatisfactory in practical applications due to the challenges in waveform design and its non-stationary property, which significantly degrades the performance of current high-resolution subspace techniques for direction of departure (DoD) and direction of arrival (DoA) angle estimation. In this paper, we first proposed a novel OFDM-LFM waveform design method based on the scale discrete Fresnel transform (SDFnT), which efficiently generates orthogonal LFM signals with unlimited number of subcarriers and can be convieniently implemented using the fast Fourier transform (FFT). Then, for angle estimation in OFDM-LFM MIMO radars, we presented a new scale discrete Fresnel transform multiple signal classification (SDFnT-MUSIC) method. By converting the steering vector into the chirp domain and making it non-time-vary, high resolution angle estimation for OFDM-LFM wideband signals can be achieved. Simulation results shows that the proposed waveform design method requires less computational time than conventional method based based on the fractional Fourier transform (FrFT), whereas the proposed DoA-DoD estimation method outperform the FrFT-MUSIC method in terms of computational complexity and target angle estimate performance.

Keywords: ofdm lfm; method; waveform design; estimation

Journal Title: IEEE Access
Year Published: 2023

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