The nonlinear frequency modulation (NLFM) waveform can achieve low sidelobes without loss of signal-to-noise ratio (SNR) by utilizing a nonlinear time-frequency structure. This letter presents a novel two-step progressive optimization framework for the NLFM waveform using Fourier series by exploiting the advantages of random searches and deterministic modifications. The modified GA is used for the preliminary design of the NLFM waveform, where random searches with waveform diversity and consideration of the signal’s characteristic provide a rapid decrease of sidelobes in early iterations. When the descent speed of the sidelobes slows down, deterministic modifications in the gradient-based tuning are followed to further reduce the sidelobes. In the simulation, the peak-to-sidelobe level ratio (PSLR) is reduced by at least 5 dB with an almost equivalent normalized impulse response width (IRW) under the same time-bandwidth product (TBP) compared with other NLFM waveforms. Finally, the optimized NLFM waveform is implemented on hardware, which verifies its performance.

In this paper, a novel pulse-agile waveform design based on random frequency modulation (RFM) waveforms is proposed for range sidelobe suppression and range ambiguity mitigation to improve the system performance of radar detection and imaging. The time-frequency relationships of the proposed RFM waveforms are characterized by random Fourier coefficients, which are different from other RFM waveform models. To determine the number and the range of random Fourier coefficients, an RFM waveform design framework based on the theoretical derivation of spectral distribution is presented. The proposed framework has the ability to generate spectral-compact pulse-agile RFM waveforms with high efficiency even under a large waveform number and a large time-bandwidth product. The designed RFM waveforms have random sidelobe, good quasi-orthogonality, high spectral compactness, and constant amplitude. By exploiting the advantage of pulse-agile RFM waveforms, range sidelobes can be reduced by the plural accumulation of the pulse compression results of multiple RFM waveforms. Meanwhile, range ambiguity can be mitigated using different filter banks for the corresponding range intervals. Compared with other low sidelobe quasi-orthogonal waveforms, the designed pulse-agile RFM waveforms using random Fourier coefficients perform better in peak-to-sidelobe level ratio (PSLR) and cross correlation peak (CCP) levels with a large waveform number. The PSLR and the average CCP level for a thousand RFM waveforms are -49.0 dB and -25.8 dB, respectively. Finally, a series of simulations and experiments of microwave imaging that transmit pulse-agile RFM waveforms are conducted, which demonstrate the ability of range sidelobe suppression and range ambiguity mitigation.

A microwave photonic (MWP) radar system with improved signal-to-noise ratio (SNR) performance is proposed and experimentally demonstrated. By improving the SNR of echoes through properly designed radar waveforms and resonant amplification in the optical domain, the proposed radar system can detect and image weak targets that were previously hidden in noise. Echoes with a common low-level SNR obtain high optical gain and the in-band noise is suppressed during resonant amplification. The designed radar waveforms, based on random Fourier coefficients, reduce the effect of optical nonlinearity while providing reconfigurable waveform performance parameters for different scenarios. A series of experiments are developed to verify the feasibility of the SNR improvement of the proposed system. Experimental results show a maximum SNR improvement of 3.6 dB with an optical gain of 28.6 dB for the proposed waveforms over a wide input SNR range. From a comparison with linear frequency modulated signals in microwave imaging of rotating targets, significant quality enhancement is observed. The results confirm the ability of the proposed system to improve SNR performance of MWP radars and its great application potential in SNR-sensitive scenarios.

The difficulty in designing quasi-orthogonal radar waveforms is to ensure low levels of autocorrelation sidelobe peak (ASP) and cross-correlation peak (CCP) under a large number of waveforms. This letter proposes a waveform model with reciprocating nonlinear frequency modulation (RNLFM) for the quasi-orthogonal waveform design. The RNLFM waveform both enjoys the low sidelobe characteristics of nonlinear frequency modulation (NLFM) and high degrees of freedom from reciprocating frequency modulation. A greedy optimization framework is presented to decompose the waveform design problem into two optimization problems that minimize ASP and CCP levels, respectively. Simulation results show that the ASP and the CCP levels of the optimized RNLFM waveforms are reduced by 5.5~9.5 dB and 0.2~2.4 dB respectively, compared with other quasi-orthogonal waveforms under the same waveform number.

The photonic frequency-interleaving (PFI) technique has shown great potential for broadband signal acquisition, effectively overcoming the challenges of clock jitter and channel mismatch in the conventional time-interleaving paradigm. However, current comb-based PFI schemes have complex system architectures and face challenges in achieving large bandwidth, dense channelization, and flexible reconfigurability simultaneously, which impedes practical applications. In this work, we propose and demonstrate a broadband PFI scheme with high reconfigurability and scalability by exploiting multiple free-running lasers for dense spectral slicing with high crosstalk suppression. A dedicated system model is developed through a comprehensive analysis of the system non-idealities, and a cross-channel signal reconstruction algorithm is developed for distortion-free signal reconstruction, based on precise calibrations of intra- and inter-channel impairments. The system performance is validated through the reception of multi-format broadband signals, both digital and analog, with a detailed evaluation of signal reconstruction quality, achieving inter-channel phase differences of less than 2°. The reconfigurability and scalability of the scheme are demonstrated through a dual-band radar imaging experiment and a three-channel interleaving implementation with a maximum acquisition bandwidth of 4 GHz. To the best of our knowledge, this is the first demonstration of a practical radio-frequency (RF) application enabled by PFI. Our work provides an innovative solution for next-generation software-defined broadband RF receivers.

A resolution-improving method for multiband imaging based on an extrapolated RELAX algorithm (ERA) is proposed. The proposed method improves image resolution by reconstructing a wideband signal through nonadjacent narrow subbands. The key points of this method are the coherent compensation of the subbands and the accurate extraction of target point scatters’ parameters from each subband. For coherent compensation, a two-step phase compensation (TSPC) is used to precisely compensate for the phase incoherence terms between the subbands. In order to accurately extract the parameters of point scatters (PSs), the ERA is proposed, which establishes a cost function between the extrapolated subbands and the PSs’ parameters. Furthermore, to enhance the robustness of PSs’ parameters extraction, a local band purification (LBP) process is proposed to resist the non-Gaussian clutter in the subbands. To validate the performance of the proposed method, Monte Carlo experiments using simulated data are carried out, whose results show that the proposed method can successfully improve the image resolution through the subbands under low signal-to-clutter ratio (SCR). Moreover, experiments with real measured data are conducted, using two 0.75 GHz subbands to reconstruct a 5 GHz signal, whose 2D image result is approximated to that based on the real 5 GHz signal. Image parameters are also compared, whose results demonstrate that the proposed method has satisfactory accuracy and robustness on improving image resolution.