The high-resolution wide-swath synthetic aperture radar (HRWS SAR) system enables achieving comprehensive and extensive ground information more accurately and rapidly, enhancing the precision of target detection, identification, confirmation, and description. A common implementation approach of it is azimuth multichannel synthetic aperture radar (SAR), which has become a research hot spot in the field of SAR in recent years. In practice, there is a situation where a channel failure leads to the loss of corresponding data, and in such cases, it is impossible to obtain a high-resolution wide-swath image of quality. Currently, there is no good method to address the data recovery issue for one channel data completely missing. To solve this problem, in this letter, a scheme based on iteration adaptive approach (IAA) and weighted least squares method is proposed for azimuth multichannel SAR missing channel data recovery. Point target simulations and data generated from airborne SAR system demonstrate that the proposed scheme is effective.

The primary technical challenge for multi-input multi-output synthetic aperture radar (MIMO-SAR) systems is separating independent channel responses from aliased echoes while maintaining imaging performance. However, the most promising short-term shift-orthogonal (STSO) and segmented-phase-code (SPC) waveform require the use of elevation digital beamforming (DBF) to achieve echo separation. The cost of using elevation DBF for echo separation is the loss of elevation degrees of freedom and a significant increase in system complexity. To solve this problem, this paper proposes a novel coded waveform that introduces phase characteristics for echo separation through two-dimensional phase encoding of the transmitted waveform in both elevation and inter-pulse (azimuth) direction. In this scheme, azimuth DBF is used in the Doppler frequency domain to suppress interference signals, while elevation phase demodulation is employed to separate the echoes. This scheme eliminates the dependence of MIMO-SAR on waveform orthogonality and allows the direct use of a large number of single-station waveforms, providing flexibility in waveform selection. Additionally, retaining more degrees of freedom enables the multi-modal operation of MIMO-SAR. Finally, detailed simulation experiments are performed to verify the potential of the proposed scheme, and advantages and contributions are systematically analyzed.

In spaceborne synthetic aperture radar (SAR) imaging, pulse repetition interval (PRI) variation technique can be used to change the position of gaps caused by transmission blockage, enabling ultrawide continuous swath SAR imaging. In particular, linear fast PRI change stands out for its ability to directly control gap positions. However, when higher resolution is required, existing linear fast PRI design strategy poses a potential risk of gap overlap, further degrading imaging quality. To tackle this problem, this letter proposes an improved linear fast PRI change design strategy for high-resolution wide-swath (HRWS) continuous SAR imaging. In the improved design strategy, a feasible region for PRI design is developed to ensure that azimuth samples are never continuously lost. Subsequently, the design strategy of more elaborated PRI sequence is improved by expanding the feasible region, which increases the flexibility of system design and improves the range ambiguity to signal ratio (RASR) performance of SAR. Finally, simulation results demonstrate the advancement of the proposed strategy, with the worst RASR of the SAR system improving by 6 dB in the given example.

Typically, synthetic aperture radar (SAR) utilizes linear frequency modulation (LFM) signal to acquire high-resolution images, requiring spectral windowing to suppress sidelobes while sacrificing signal-to-noise ratio (SNR). In contrast to LFM signal, nonlinear frequency modulation (NLFM) signal can reconstruct the signal power spectral density (PSD) without sacrificing SNR, providing autocorrelation outputs with lower sidelobes. Despite the excellent application potential of NLFM signal, the real-time generation of NLFM faces numerous challenges due to the high complexity of the systems involved and constraints imposed by waveform generator devices. In this letter, a low-complexity, high-precision and high-resolution intermediate-frequency NLFM signal generation device is developed, requiring only eleven parameters to generate real-time NLFM signal of arbitrary time width and bandwidth, with a maximum bandwidth reaching 1.2 GHz. This NLFM signal generator will be employed in the unmanned aerial vehicle (UAV) SAR system. Finally, the performance of the NLFM signal generator has been validated through ground experimental results.

The echo separation issue of different transmit antennas is the most technical challenge in realizing multiple-input and multiple-output synthetic aperture radar (MIMO SAR) with same frequency band, especially for low-computing echo separation, making it extremely difficult towards the practical application for the spaceborne MIMO SAR. Based on the orthogonal frequency-division multiplexing (OFDM) chirp waveforms, this letter proposes an innovative echo separation scheme with digital beamforming (DBF) and bandpass filtering (BPF) on board and bandpass-null steering on the ground for the spaceborne MIMO SAR. This scheme transfers the complex computing process on board to the ground, thus significantly reduce the computational load and relieve the resource occupation on board. Also, the perfect separation of interested echoes from interference can be achieved by this scheme. Finally, performance comparisons and simulation results show the effectiveness of the proposed scheme. The proposed scheme enables a high-efficiency and great-performance echo separation for the spaceborne MIMO SAR and makes the MIMO SAR a more promising technique for future SAR missions.

High-resolution wide-swath (HRWS) imaging has always been a primary demand for synthetic aperture radar (SAR) remote sensing. Multiple-input multiple-output (MIMO) is a feasible scheme for achieving HRWS imaging and is a hot research topic among scholars. However, in contrast to classic single-input multiple-output (SIMO) SAR, MIMO-SAR schemes require the isolation of transmitted waveforms. The transmitted waveforms and the corresponding echo separation methods are essential techniques in MIMO-SAR. Orthogonal frequency-division multiplexing (OFDM)-chirp waveforms and an OFDM-beamforming (OB) method have been proposed, but have not been validated experimentally. In this letter, an airborne X-band digital beamforming (DBF)-SAR system is used to demonstrate MIMO-SAR with improved OFDM-chirp waveforms for the first time. Experimental results of frequency- and spatial-domain methods demonstrate that the mixed echoes can be effectively separated by OB scheme. The utilization of bandpass filters (BPFs) in OB scheme can conserve computation resources. Signal-to-interference ratio (SIR) is employed to test the performance of BPFs, where the indicator shows that the SIR loss is within 0.2 dB.

Digital beamforming (DBF) is an effective approach for accessing high-resolution wide-swath (HRWS) imaging in spaceborne synthetic aperture radar (SAR). By utilizing DBF, the performance of imaging, including signal-to-noise ratio (SNR) and system sensitivity, can be greatly improved. In actual missions, DBF for SAR imaging can be combined with various operating modes like squint-strip SAR, spotlight SAR, and TOPSAR. In squint-looking scenarios, the receiving beam of the antenna scans the scene not only along the vertical direction (elevation) but also along the horizontal direction (azimuth). For the first time, this article proposes the application of DBF for squint SAR imaging, establishes a geometric model of beam scanning, and derives the analytic expression of the signal model. The performance of both the conventional DBF scheme and the digital scalloped beamforming (DSBF) scheme is analyzed in squint-looking scenarios. In order to further reduce the loss of gain when processing received signals with broadband widths and long pulse durations in the conventional DBF schemes, as well as to minimize the digital resource consumption in the DSBF scheme, where the resource usage is directly proportional to the number of subbeams, a novel multibeam DBF scheme is proposed. Theoretical analysis and simulation results validate the effectiveness of the proposed scheme, making it as a more realistic technology for future spaceborne SAR.

Range ambiguity suppression is a key technical challenge for synthetic aperture radar (SAR) systems. Waveform diversity technology is a potential solution due to its low system complexity. In this letter, a 2-D method based on orthogonal nonlinear frequency modulation (NLFM) waveform and azimuth phase coding (APC) for range ambiguity suppression is proposed. This approach not only suppresses range ambiguity energies instead of dispersing them, but also works for multiple consecutive orders of range ambiguity energies. The imaging processing and range ambiguity suppression performance are described in detail. In addition, the range-ambiguity-to-signal radio (RASR) is analyzed, and the simulation results for the point target and distribution scenarios are given to verify the effectiveness and practicality of the proposed scheme.

Frequency diverse array synthetic aperture radar (FDA-SAR) has been recognized as a potential technique for high-resolution wide-swath imaging, and employs a slight frequency increment to the transmitting sub-apertures/channels to form a range-dependent beam pattern for swath widening. The key challenge of FDA-SAR is echo separation at the receiver. Former studies have employed quasi-orthogonal waveforms with low cross-correlation energies as the transmitted signals, which can not ensure reliable echo separation, especially for distributed scatterers. In this letter an FDA-SAR processing framework is proposed based on the segmented phase code waveform. An encoding scheme and a notch-expanding receiving beamformer based on convex optimization are used for precise echo separation. Then, using the degrees of freedom on transmitting, a beamformer is applied to resolve range ambiguities. The proposed scheme avoids the performance deterioration caused by the echo separation issue, even for distributed scatterers, while allowing other multiple-channel techniques to be integrated. Simulation experiments have validated the effectiveness of the proposed scheme.

Digital beamforming (DBF) can provide high-gain narrow-beam scanning reception while transmitting wide-beam signals, which greatly improves the signal-to-noise ratio (SNR) of the corresponding systems. It is an effective technique for synthetic aperture radar (SAR) to obtain high-resolution wide-swath (HRWS) imaging capability. However, elevation changes in mountain area will lead to beam-pointing mismatch problems when using the ideal sphere model to calculate the beamforming weighting vector. As a result, the loss of receive gain and the deterioration of the SNR will occur. To solve this problem, adaptive DBF (ADBF) methods based on spectral estimation are typically used, such as Capon and MUSIC. However, the computational complexity of spectral estimation method is high, which is not conducive to on-satellite real-time processing. Therefore, a low complexity ADBF method based on beam-space phase-center cross correlation is proposed. In this method, the whole array is divided into several subarrays, and multiple phase centers are formed by beamforming so that the angle of arrival (AOA) of the signal source can be accurately estimated. Then, the weighted vector of the received beam is updated to mitigate the loss of receiver gain. The simulation results and airborne measured data validate the effectiveness of the proposed method. Compared with methods based on Capon and MUSIC, the proposed method can decrease the computational complexity without reducing the processing accuracy, thus providing a basis for the real-time processing of spaceborne DBF-SAR signals in the future.

Space-Time Waveform-Encoding (STWE)-synthetic aperture radar (SAR) enables waveform diversity in the space-time domain to meet the requirements of future high-resolution and wide-swath (HRWS) missions. The STWE-SAR receives echoes from multiple sub-swaths simultaneously with a single receive window. The overlapping echoes are usually separated based on the linear constrained minimum variance (LCMV) beamformer. However, the energy of the echoes from different sub-swaths can have a huge difference in the time domain. The conventional LCMV beamformer cannot effectively separate the overlapped echoes because the echo energy difference is not considered. Based on airborne STWE-SAR data, this paper performs energy equalization pre-processing before echo overlapping. Moreover, this paper confirms that the echo discrepancy is worth considering in the STWE system by comparing the separation results of the LCMV beamformer before and after energy equalization. This paper recommends that the design of future echo separation schemes needs to focus not only on the echo arrival of angle but also on the echo energy based on the actual situation.

Nonlinear frequency modulation (NLFM) signal can construct the signal’s power spectral density to reduce sidelobes without loss of signal-to-noise ratio. LuTan-1 (LT-1) is an L-band spaceborne synthetic aperture radar mission which is launched in the beginning of 2022, and a high-precision NLFM signal generator is developed in LT-1. However, the existing model, i.e., the traditional frozen ionosphere model, can not accurately describe ionospheric dispersion effects faced by the NLFM signal due to the non-linear characteristic of the instantaneous frequency. Thus, an extended model is established in this paper to describe ionospheric dispersion effects of the NLFM signal. Then, the differences of ionospheric dispersion effects on the NLFM and linear frequency modulation signals are compared. Afterwards, a method that embedded into the focusing procedure is proposed, which aims to eliminate ionospheric dispersion effects for the NLFM signal. Finally, the hardware-in-the-loop simulations of point targets and distributed targets are performed to verify the proposed method. The method proposed in this paper is used in the ground processing system of LT-1.

Synthetic aperture radar (SAR) systems require a favorable waveform for imaging as the radar waveform directly affects the performance of SAR systems, such as image quality and resolution. It is well known that the nonlinear frequency modulation (NLFM) waveform can adjust the time-frequency relation to shape the power spectral density (PSD) and then provide a matched filtering output with lower sidelobes without losing signal-to-noise ratio (SNR). However, it will broaden the main lobe, which means the resolution of the SAR image decreases. Therefore, in this paper, a novel NLFM waveform is proposed. It employs the piecewise linear function (PWL) model to define the instantaneous chirp rate function, and genetic algorithm (GA) is then applied to optimize the waveform. The novel NLFM waveform promises enhanced performance and flexibility due to greater design freedom. Through this method, lower sidelobe is achieved within the same 3-dB main lobe width. Finally, simulation results are presented to verify the practicability of the proposed NLFM waveform.

The nonlinear frequency modulation (NLFM) waveform is a promising candidate for the linear frequency modulation (LFM) signal because its autocorrelation output exhibits low sidelobes without loss of signal-to-noise ratio (SNR), also avoiding the transmitting power loss for spaceborne synthetic aperture radar (SAR). However, the acquisition of the analytical expression of the NLFM waveform is often closely related to the indirect instantaneous frequency function generated by the principle of stationary phase (POSP), thus it is not inconvenient for the real-time generation of the efficient and precise NLFM signal on board. In this letter, based on the harmonic decomposition, closed-form expressions of the NLFM waveform, which are directly calculated by the predefined window, are derived in both time and frequency domains. Therefore, it is very beneficial to the real-time generation and process of the NLFM waveform for the SAR system. All the simulation results and analyses validate the promising potential of the closed-form expressions of the NLFM waveform for SAR application.

The conventional reconstruction algorithm allows for unambiguous recovery of the Doppler spectrum of multichannel synthetic aperture radar (SAR) system in azimuth with an accurately known channel response matrix. However, the available knowledge of the actual channel response matrix is imprecise due to channel errors. In this case, the SAR image will suffer from severe error-induced azimuth ambiguities if reconstructed by the conventional reconstruction algorithm, especially for the case of closely singular sampling. To this end, a novel method based on a quadratically constrained quadratic program (QCQP) optimization is proposed to increase the robustness to the channel errors. Accordingly, the error-induced azimuth ambiguities can be greatly suppressed by the proposed method. Furthermore, performance comparisons of the conventional reconstruction algorithm and the proposed method via numerical simulation are presented.

Digital beamforming (DBF) is a fundamental technique for synthetic aperture radar (SAR) to get high-resolution wide-swath (HRWS) images, which significantly increases the signal-to-noise ratio (SNR) of the system and improves range ambiguity performance. Moreover, the performance of the DBF-SAR system can be improved by using the nonlinear frequency modulation (NLFM) waveform, which can provide a matched filtering output with lower sidelobes without the loss of SNR compared to the linear frequency modulation (LFM) waveform. Combining the DBF technique and the NLFM waveform will enhance the system performance of DBF-SAR from an additional degree of freedom, which has essential engineering significance for reducing the transmit power of the system. However, the previous system architecture and processing method of DBF-SAR are generally based on the LFM waveform and are not practicable in DBF-SAR adopting NLFM waveform. This manuscript demonstrates the potential of adopting the NLFM waveform in DBF-SAR and analyzes the problems of compensating pulse extension loss (PEL) and frequency dispersion loss (FDL) in the new system. Then, an optimized DBF framework that combines sub-digital beamforming and a bank of unequal-width bandpass filters to suppress PEL and FDL in DBF-SAR adopting NLFM waveform is proposed. Simulations demonstrate that the proposed framework shows greater efficiency and stability in suppressing the severe PEL and FDL in the NLFM and LFM systems than previous methods. This manuscript brings an additional degree of freedom to the next generation spaceborne DBF-SAR and provides sufficient technical support for high-performance DBF-SAR when the LFM waveform is not adopted.

Synthetic aperture radar (SAR) is an advanced ground-observing remote sensing technology, and high-resolution wide-swath (HRWS) imaging has always been the goal of SAR. In general, an improved azimuth resolution requires a large pulse repetition frequency (PRF), resulting in high system requirements. To overcome this difficulty, azimuth multichannel technology has gradually developed, achieving HRWS imaging and decreasing the PRF by increasing the spatial sampling, i.e., increasing the number of antenna subapertures in the azimuth. This article proposes a theoretical architecture that generates multiple virtual receiving apertures in the azimuth rather than real apertures. The virtual receiving apertures are formed by multiplying the azimuth signals by linear phase histories provided by vortex beams carrying different orbital angular momentum (OAM) modes. Vortex beams with different OAM modes have different oblique phase wavefronts, so virtual receiving positions are generated in the along-track direction. This approach aims to reduce the PRF without increasing the azimuth real receiving aperture. Simulation results demonstrate the effectiveness and limitations of the method. Finally, to overcome the inherent limitations of the method, two possible implementation schemes are proposed.

The non-linear frequency modulation (NLFM) waveform can shape the power spectrum such that its autocorrelation output exhibits very low sidelobes without loss of signal-to-noise ratio (SNR), compared with the linear frequency modulation (LFM) waveform. However, the NLFM waveform has attained little acceptance in spaceborne SAR system due to its distinct disadvantages, e.g., greater system complexity and limited development of the NLFM generation devices. In this paper, we report a parametric piecewise linear (PWL) model for the generation of the general NLFM waveform. Through this model, a novel generation approach, which can significantly reduce the signal computing resources on board, is proposed. Nevertheless, the existed advanced NLFM waveforms, which possess a lower sidelobe under fixed main lobe, suffer from severe performance degradation with this parametric model. To this end, an empirically advanced NLFM waveform is further proposed. This proposed waveform not only allows for a low computing complexity generation by a modified parametric PWL model, but also its performance degradation is dramatically reduced. Finally, detailed simulation experiments are performed to verify the excellent performance of the proposed NLFM waveform.

Multiple-input and multiple-output synthetic aperture radar (MIMO SAR) is a very potential technique for high-resolution and wide-width (HRWS) imaging due to the fact that it can provide more degrees of freedom. In this paper, an innovative MIMO-HRWS SAR imaging system is introduced with segmented phase coding (SPC) waveforms. However, it is well known that the echo separation issue is the most technical challenge for MIMO SAR. It has shown that the separation of orthogonal echoes from cross-correlation interference can be achieved by scan-on-receive (SCORE). However, this method often requires large computing resources on board, especially for null-steering process. For this, we propose a two-stage spaceborne-ground echo separation scheme. This scheme is mainly divided into two-steps: the first step is a real-time SCORE-beamforming process on board to reduce the downlink data volume, and the second step is a bandpass-null steering process to suppress the interfering echoes on the ground. Thus, this scheme allows for the low computing resources on board and sufficient suppression of the interference simultaneously. Following this scheme, the MIMO-HRWS SAR system enables its number of equivalent phase centers nearly double that of the azimuth multichannel SAR system, thus higher-resolution and wider-swath imaging. Finally, detailed simulation experiments for the MIMO-HRWS SAR imaging system are performed to verify the practicability and feasibility of the proposed scheme.

Multiple-input–multiple-output synthetic aperture radar (MIMO-SAR) has extensive application prospects, mainly including the acquisition of multidimensional scattering information, high-resolution and wide-width (HRWS) imaging, and moving target indication (MTI). Its echo separation is the most technical challenge, and so far, the confirmation for orthogonal waveform encoding MIMO-SAR by airborne experiments has not been reported in any literature. Here, an echo separation experiment based on the segmented phase code (SPC) waveforms and an airborne digital beamforming SAR (DBF-SAR) system is demonstrated for the first time. In the experiment, the SPC waveforms are cyclically transmitted within the adjacent pulse repetition intervals (PRIs) to simulate multiple transmitters, and the scattered echoes are received by the 16-channel antennas in elevation at the same time. In the postprocessing, the echo signals of continuous PRIs are added to obtain the mixed echoes, and a detailed echo separation method is adopted. In the method, the mixed echo signals from close arrival angles and far arrival angles are separated by the time shift and weighting, and by the bandpass filtering and DBF technique, respectively. Through the presented method, the mixed echoes of dual-transmit and 16-receive (2T16R) SAR imaging mode are separated and imaged successfully. The experimental results not only validate the echo separation scheme but also indicate that it is very promising in future MIMO-SAR missions.

Hybrid and$\pm \pi /4$quadrature-polarimetric (quad-pol) synthetic aperture radar (SAR) systems are established to simultaneously obtain all polarimetric components, including co-polarized (co-pol) and cross-polarized (cross-pol) components. However, the cross-pol components always suffer from severe azimuth ambiguities. In this article, the hybrid and$\pm \pi /4$quad-pol SAR systems with double receive channels are widely investigated to suppress the azimuth ambiguities of cross-pol components, in which the systems allow for a half pulse repetition frequency but at the cost of antenna size. We firstly provide a more thorough analysis for the double-channel (DC) hybrid and$\pm \pi /4$quad-pol SAR systems. Then, an improved reconstruction method is proposed to suppress the extremely severe azimuth ambiguity caused by the general reconstruction algorithms. However, the cross-pol signals still exist severe azimuth ambiguity. To this end, the displaced-phase-center antenna (DPCA) condition based on digital beamforming reflector antenna is employed, in which the undesired polarized signal can be greatly suppressed. Furthermore, numerical analysis is developed to demonstrate the excellent performance of the DC hybrid and$\pm \pi /4$quad-pol SAR systems with such DPCA condition. Finally, the distributed scene simulation results are presented to verify the advantage of the proposed approach.

In recent years, the multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) concept has been widely researched because it can provide more degrees of freedom to dramatically improve SAR system performance. However, the echo separation issue of different transmit antennas is the most challenging issue and it stirs up extensive discussions. In this letter, a novel MIMO-SAR imaging scheme based on the improved orthogonal frequency-division multiplexing (OFDM) waveforms is proposed. The main contributions of this work are that:1)Improved generation method for$M$OFDM waveforms is presented. This method can compensate the extra carrier frequency deviation and compared with the other compensation methods, this method is more general and suitable for$M$OFDM waveforms.2)Based on the proposed OFDM waveforms, a novel and low-cost spaceborne MIMO-SAR imaging scheme is proposed.In this scheme, a simple time-shift weighting process and a bandpass filter bank are employed to separate the echoes from the close arrival angles. Then, the digital beamforming (DBF) on receive in elevation is employed to separate the echoes from far arrival angles. Furthermore, the distributed scene simulation results are presented to verify the practicability of the proposed scheme.

In this letter, a novel and low-cost echo separation technique for the multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) is presented, based on the orthogonal frequency-division multiplexing (OFDM) chirp waveforms. The proposed scheme allows the generation of multiple OFDM chirp waveforms on common spectral support. In the new scheme, a series of simple time-domain operations including replica, T-shift, and superposition is applied to eliminate the interference waveform within a limited time. Then, a combination with a bandpass filter instead of a matched filter to focus signal power and digital beamforming (DBF) on receive in elevation enables the suppression of interference signals for a realistic spaceborne SAR scenario, where the swath width exceeds the spatial extension of the transmitted pulse. Furthermore, the distributed scene simulation results are presented to verify the practicability of the proposed scheme.

The echo separation issue associated with different transmit antennas is the most technical challenge in realizing the multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) system. In this article, a novel MIMO-SAR imaging scheme based on an advanced radar waveform, namely, segmented-phase-code (SPC) waveform, is proposed. Compared with the state-of-the-art short-term shift-orthogonal (STSO) waveform beamforming schemes, this scheme relieves the short-term shift-orthogonality condition of transmitted waveforms without losing the imaging performance, which extends the optional waveform space. In this scheme, the separation of the echoes from close arrival angles is ensured by a simple time-shift weighting processing. Furthermore, a range bandpass filter bank and the digital beamforming (DBF) technique are employed to ensure that the echoes from far arrival angles are separable. Finally, detailed simulation experiments are performed to verify the feasibility of the proposed scheme, and in-depth discussions of different waveforms and MIMO-SAR imaging schemes are presented.

The azimuth phase coding (APC) technique is known for its very low implementation complexity and its effectiveness for point and distributed ambiguities in conventional synthetic aperture radar (SAR) systems. In recent years, as an extension, the APC technique has been briefly discussed for multichannel SAR systems. However, the properties of the APC technique are no longer guaranteed in the multichannel SAR systems based on the digital beamforming (DBF) on-receive, and only a slight APC gain in the suppression of the range ambiguity can be obtained. In this article, we first provide a more thorough analysis for an APC-multichannel SAR system with respect to a uniform pulse-repetition frequency (PRF). Then, the APC/multichannel SAR system with nonuniform spatial sampling is briefly discussed, and an improved reconstruction approach based on a quadratically constrained optimization model is proposed to increase greatly the APC gain with respect to existing multichannel reconstruction algorithms. This proposed approach allows the minimization of the range ambiguity with a given azimuth-ambiguity constraint. In particular, for some specific PRFs, the proposed method permits a cancellation of the odd-order range ambiguity. Finally, simulation experiments are performed to verify the advantages and effectiveness of the proposed approach.

For synthetic aperture radars (SARs), an alternate transmitting mode based on waveform diversity is widely discussed for suppressing range-ambiguity in many letters, because it is easy to implement and there is no need to improve the pulse repetition frequency (PRF). These studies mainly focus on the discussion of pseudo-orthogonal waveform design, such as up-down chirp waveforms and orthogonal-frequency-division-multiplexing (OFDM) waveforms; however, the effect on imaging caused by waveform diversity is ignored. This letter, for the first time, provides a demonstrative derivation of imaging for the alternate transmitting mode, which will deepen the understanding of this mode and be helpful for the future research. In this letter, we point out that transmitting different waveforms will introduce a phase-amplitude periodic modulation in the azimuth domain; furthermore, it will cause the aliasing of the azimuth spectrum. In addition, the simulation experiment is performed for verifying the correctness of the theoretical analysis.

It is well known that the nonlinear frequency modulation (NLFM) chirp waveform can shape advantageously the power spectrum density (PSD) such that the autocorrelation function exhibits reduced sidelobes as the window function. However, differences between the PSD and window function due to the Gibbs effects caused by the Fresnel integral would lead to deteriorative performance of the NLFM chirp waveform. In particular, the correlation function of NLFM waveform with Chebyshev PSD is seriously inconsistent with the lowest sidelobe level of the Chebyshev window function possesses. To overcome the inconsistency, therefore, in this letter, a novel NLFM waveform with modified Chebyshev window PSD is proposed, which combines the Chebyshev with edge distortion compensation, allowing, in theory, low sidelobe level as Chebyshev window. Using theoretical analysis also confirmed by simulation, this letter shows that the novel NLFM waveform possesses low sidelobes without high computational complexity in design.

This article establishes a multiobjective optimization model to suppress the azimuth ambiguity power and noise simultaneously in signal reconstruction for a multichannel synthetic aperture radar (SAR) system. This multiobjective optimization model extends the theory of multichannel signal processing for reconstructing the SAR signal from the aliased signals. Linear scalarization and a quadratically constrained method for the multiobjective optimization model are applied to obtain l1norm optimization, l2norm optimization, and quadratically constrained optimization, respectively, in signal reconstruction. Azimuth ghosts can intuitively reflect the effects of azimuth ambiguity on SAR images. The l1norm optimization solution leads to a minimum upper bound of azimuth ghosts. A lowest azimuth ambiguity-to-signal ratio (AASR) can be derived by l2norm optimization. By relaxing the constraint of total ambiguity power suppression, one can obtain a minimum noise level in the case of quadratically constrained optimization. The reconstruction performances of the multiobjective optimization model in terms of AASR, signal-to-noise ratio (SNR), and signal-to-ambiguity-plus-noise ratio (SANR) are investigated with respect to the pulse repetition frequency (PRF) and compared with other methods for a multichannel SAR system.

It is well known that the nonlinear frequency modulation (NLFM) waveform with the advantage that it can shape the power spectral density (PSD) to provide a radar matched filter output with lower sidelobe without the loss of signal-to-noise ratio (SNR) when compared with the linear frequency modulation (LFM) waveform. But NLFM waveform would also broaden the main lobe and reduce the range resolution. In this paper, we report a novel waveform optimization framework. Through this framework, an advanced nonlinear frequency modulation (NLFM) waveform with lower sidelobes and a smaller main lobe is constructed. In addition, we apply it in a real synthetic aperture radar (SAR) system with a bandwidth of 100 MHz at 9.6 GHz carrier frequency and the imaging results validate the proposed NLFM waveform.

Range ambiguity suppression is a technical challenge for current synthetic aperture radar systems. A potential solution is to orthogonally modulate the transmitting pulses; however, these orthogonal waveforms (e.g., up-down chirp waveforms) actually cannot reduce the cross correlation energy (CCE). Nonlinear frequency modulation (NLFM) waveform can change the time-frequency relationship to adjust the energy distribution within the bandwidth to reduce the CCE. In this letter, a novel orthogonal NLFM waveform optimization framework is proposed. Through this framework, advanced NLFM waveforms with low sidelobe and CCE are constructed. Furthermore, point and distributed scene simulation results are presented to verify the practicability of the proposed waveforms. In addition, the system scheme, waveform design, and range ambiguity suppression performance are detailed.

Generally, synthetic aperture radar (SAR) system transmits linear frequency modulation (LFM) signal to obtain the high-resolution image and weighted windowing is usually employed to suppress sidelobes. However, it will cause a 1-2-dB signal-to-noise ratio (SNR) loss. Nonlinear frequency modulation (NLFM) signal, which can construct the signal's power spectral density (PSD) to reduce sidelobes without loss of SNR, is a promising candidate. However, the real-time generation of precise NLFM signal is still a technical challenge. In this letter, a high-precision NLFM signal generator with the ability of predistortion compensation is developed, and this signal generator will be employed in LuTan-1 (LT-1, i.e., TwinSAR-L) mission which is an innovative spaceborne bistatic SAR mission and planned to launch in 2020. In addition, a two-step error compensation method is developed to compensate the system error. Finally, the ground experiment is performed to validate the designed signal generator.

With the development of high-resolution radar satellite for global comprehensive environmental monitoring, day-and-night and all-weather surveillance has become an active and growing research field. However, in all cases, these applications require radar to have a high-efficiency radar module (e.g., T/R module), and high system transmitting power. These requirements may put an important limitation on the performance of a radar satellite with a high-power configuration. In this paper, we report a novel waveform optimization framework. Through this framework, an advanced nonlinear frequency modulation (NLFM) waveform with lower sidelobes and a smaller main lobe, which can significantly relieve the restriction of very limited satellite power, is constructed. In addition, we apply it in a real synthetic aperture radar (SAR) system with a bandwidth of 100 MHz at 9.6-GHz carrier frequency and the whole process of the NLFM waveform for radar imaging is discussed in detail, including the system architecture and configuration, a system error compensation method, and a modified chirp scaling algorithm (CSA). The imaging results demonstrate the excellent performance of the advanced NLFM waveform. Moreover, we observe that the SAR system with the advanced waveform has a higher signal-to-noise ratio (SNR) of 1.29 dB compared with the conventional linear frequency modulation (LFM) waveform. The improvement of 1.29-dB SNR means that the real radar system can reduce transmitting power with a ratio of 25%. This effect is likely to be a potential feature of NLFM waveform, which can reduce the transmitting power requirement, especially for radar satellite.