Caicai Gao

Orthogonal Frequency Diversity Waveform with Range-Doppler Optimization for MIMO Radar

In this letter, we modify the transmitted signal of the discrete frequency coding waveform with linear frequency modulation (DFCW-LFM) for multiple-input multiple-output (MIMO) radar from contiguous subpulses to an inconsecutive pulse train. The range-Doppler map is obtained by performing fast Fourier transform (FFT) after the transmit beamformer to detect the moving target. The cost function of the genetic algorithm used to optimize the carrier frequency sequence is obtained by minimizing both the range-Doppler sidelobes and cross-correlation peaks. Compared with the DFCW-LFM, the proposed waveform has lower autocorrelation sidelobes and cross-correlation for the delay within the subpulse duration.

Piecewise LFM waveform for MIMO radar

To separate the received signals in a multiple-input multiple-output (MIMO) radar, the transmitted signals should be orthogonal or have a low cross-correlation level. Some other properties, such as low autocorrelation sidelobes, high range resolution, and good Doppler tolerance are also desired. However, they are difficult to achieve simultaneously. In general, an improved criterion is at the cost of another degraded one. In this paper, we propose a piecewise linear frequency modulation (PLFM) waveform for the MIMO radar. The transmitted signals are pulse trains, including diversified subpulses, which are divided into three segments with controllable durations and bandwidths. The duration sequence of the second segment is obtained by the genetic algorithm to optimize the cross correlation. Theoretical analyses and numerical results are presented to illustrate the properties of the proposed PLFM waveform. Compared with the polyphase coding and the discrete frequency coding waveforms, the PLFM waveform has a lower cross-correlation level and higher degrees of freedom. The relationship of the bandwidths among different segments can be used to adjust the sidelobe peak and the main lobe width of the autocorrelation function.

Frequency coding waveform with segment LFM

In this paper, we propose a frequency coding waveform with segment linear frequency modulation (LFM) signal for the multiple-input multiple-output (MIMO) radar. This new waveform is modified from the discrete frequency coding waveform with LFM (DFC-LFM) by changing the subpulse from the LFM signal to segment LFM and extending the contiguous waveform to a pulse train. Compared to the existing frequency coding waveforms, the proposed waveform has lower autocorrelation sidelobes and lower cross correlation.

Robust space-time adaptive processing for nonhomogeneous clutter in the presence of model errors

In this paper, we first develop a novel array self-calibration method for estimating array gain-phase errors by computing the clutter subspace from the radar system parameters and using the clutter data in space-time adaptive processing (STAP). The proposed algorithm is shown to perform well even in nonhomogeneous clutter, and it can improve the performance of existing STAP algorithms, such as the clutter subspace-based method in the presence of array gain-phase errors.We also develop a two-stage STAP approach for suppressing nonhomogeneous clutter in the presence of model errors in addition to array gain-phase errors. In our two-stage STAP approach, the first stage explores the clutter subspace calculated from the radar system parameters to suppress the main clutter. The second stage employs the conventional method, such as the partially adaptive sample matrix inversion STAP method, to remove any residual clutter. Numerical results illustrate the benefits of the array self-calibration method and the effectiveness of the two-stage STAP method. Finally, the performance of the three STAP methods is compared via the well-known MCARM data set. The results further confirm that there is an improvement in performance when using array self-calibration together with the two-stage STAP method.

Piecewise Nonlinear Frequency Modulation Waveform for MIMO Radar

We propose a piecewise nonlinear frequency modulation (PNLFM) waveform for a multiple-input multiple-output (MIMO) radar. Each subpulse in the waveform set is divided into three segments. The first and the third segments are linear frequency modulation (LFM) signals, whereas the second segment is a nonlinear frequency modulation (NLFM) signal. The bandwidths and durations of subpulses are the same, whereas they can be different for each segment in the subpulse. In addition, the nonlinear time–frequency function of the second segment is controlled to improve the range and Doppler sidelobe suppression. A genetic algorithm is implemented to optimize the performance by maximally suppressing the autocorrelation sidelobe and cross correlation in range, Doppler, and angle. The MIMO radar performance is demonstrated via computation of the ambiguity function, autocorrelation function, and cross-correlation function. Numerical results are presented to show waveform properties and to compare with some existing MIMO radar waveforms. The proposed PNLFM waveform has low autocorrelation sidelobes and low cross correlation in range and Doppler, which sits at a level determined largely by the chosen time–bandwidth product.

A fast-time coding waveform design method and a bound on cross-correlation

The transmit waveforms in multiple-input multiple-output (MIMO) radar are required to have low cross-correlation for the discrimination of the waveforms in the receiver. In this paper, we develop a new fast-time coding waveform design method for sets of waveforms greater than two. The method is based on using waveforms with different chirp rates and time shifts. In addition, with the constraint that the waveforms have a flat spectrum, we prove that the average cross-correlation between any two fast-time coding waveforms is constant and related to the time-bandwidth product. Moreover, we derive a lower bound for the maximum cross-correlation between any two fast-time coding waveforms, which is also related to the time-bandwidth product. Simulation results show that any two waveforms in the developed set have a flat cross-correlation level that is nearly equal to the lower bound. Moreover, simulation results are conducted to show the range-angle map of the developed waveforms.

Double-Modulated Frequency Modulation Waveforms for MIMO Radar

We propose a double-modulated frequency modulation waveform for multiple-input multiple-output radars. The transmitted waveforms are divided into two segments with the same bandwidth and different durations. The durations of all the segments among different waveforms are used to optimize the performance. Theoretical analyses are provided to study the relationships between the autocorrelation/cross-correlation functions and parameters such as bandwidth, pulse duration, and segment durations. Numerical results show that the proposed waveform has low cross correlation even with Doppler shifts. The autocorrelation sidelobes, cross-correlation levels, and range sidelobes of the proposed waveform reduce with the increase in the time-bandwidth product.

Frequency diversity waveform with NLFM signals

In this paper, we propose a frequency coding waveform with a nonlinear frequency modulation (NLFM) signal for the multiple-input multiple-output (MIMO) radar. The transmitted signal of each transmitting antenna is a pulse train, of which, the sub-pulses are NLFM signals with different carrier frequencies. The frequency sequence and the parameter of the nonlinear frequency function are optimized to reduce the autocorrelation sidelobe and cross-correlation peaks. Compared to the existing frequency coding waveforms, the autocorrelation sidelobes and the cross-correlation level of the proposed waveform are improved significantly. In addition, with this new waveform, the ambiguity functions with sharp shape are achieved and the cross ambiguity functions have good Doppler tolerance.