High Range Sidelobes Research Articles

High-Resolution Wideband Waveform Design for Sonar Based on Multi-Parameter Modulation

The design of transmitting waveforms is an effective way to improve the detection performance of sonar systems. For the problem of high-range sidelobe when designing reverberation-resistant waveforms, this paper proposes a high-resolution wideband composite waveform design with reverberation suppression performance and a waveform parameter improvement method. Firstly, we propose a novel wideband waveform, which utilizes linear frequency modulation (LFM) as the fundamental pulse, referred to as multi-parameter coded modulation LFM pulse (MPCM-LFM). Additionally, we deduce the wideband ambiguity function for waveform design. Then, we deduce the constraint relations of the waveform parameters for different sub-band overlaps, and according to the mathematical expressions of the obtained range ambiguity function, we analyze in detail the effects of the waveform parameters on the range ambiguity function under different constraints. Secondly, on the basis of the analysis, we also propose a hopping carrier frequency constraint rule to optimize the spectral performance, and the range sidelobe is restrained effectively in significant measure by this parameter improvement method. Finally, we analyze the computer simulation results. It is obvious that our proposed waveform parameter improvement method leads to good results. The proposed improved MPCM-LFM signal shows a “near-thumbtack” ambiguity function, whose sidelobe suppression performance is superior to other classical waveforms in the desired region, and it can realize high-precision parameter estimation. In addition, the proposed improved MPCM-LFM signal possesses good performance in detecting stationary and low Doppler targets in the background of reverberation.

Binary-Phase vs. Frequency Modulated Radar Measured Performances for Automotive Applications.

Radars have been widely deployed in cars in recent years, for advanced driving assistance systems. The most popular and studied modulated waveform for automotive radar is the frequency-modulated continuous wave (FMCW), due to FMCW radar technology's ease of implementation and low power consumption. However, FMCW radars have several limitations, such as low interference resilience, range-Doppler coupling, limited maximum velocity with time-division multiplexing (TDM), and high-range sidelobes that reduce high-contrast resolution (HCR). These issues can be tackled by adopting other modulated waveforms. The most interesting modulated waveform for automotive radar, which has been the focus of research in recent years, is the phase-modulated continuous wave (PMCW): this modulated waveform has a better HCR, allows large maximum velocity, permits interference mitigation, thanks to codes orthogonality, and eases integration of communication and sensing. Despite the growing interest in PMCW technology, and while simulations have been extensively performed to analyze and compare its performance to FMCW, there are still only limited real-world measured data available for automotive applications. In this paper, the realization of a 1 Tx/1 Rx binary PMCW radar, assembled with connectorized modules and an FPGA, is presented. Its captured data were compared to the captured data of an off-the-shelf system-on-chip (SoC) FMCW radar. The radar processing firmware of both radars were fully developed and optimized for the tests. The measured performances in real-world conditions showed that PMCW radars manifest better behavior than FMCW radars, regarding the above-mentioned issues. Our analysis demonstrates that PMCW radars can be successfully adopted by future automotive radars.

Joint Radar and Communications Waveform Design Based on Complementary Sequence Sets

The joint radar and communications (JRC) waveform often has a high range sidelobe, which will degrade the target detection performance of an automotive JRC system. To solve this problem, a joint radar and communications complementary waveform group (JRC-CWG) design method is proposed in this paper by exploiting the philosophy of the complementary sequence. In the JRC-CWG, the traditional unimodular communications waveforms, such as the binary phase shift keying (BPSK) waveform, are used to perform the communications function. The sum of the autocorrelation function (SACF) of JRC-CWG is optimized to minimize the sidelobe level. Furthermore, considering that the JRC-CWG has poor Doppler resilience, a Doppler-resilient joint radar and communications complementary waveform (DR-JRC-CWG) design method is proposed to improve the Doppler resilience. Finally, the simulation results show that the proposed JRC-CWG and DR-JRC-CWG have superior radar performances without the degradation in communications performance in terms of the bit error rate (BER).

Integrated Radar and Communications Waveform Design Based on Multi-Symbol OFDM

Integrated radar and communications (IRC) technology has become very important for civil and military applications in recent years, and IRC waveform design is a major challenge for IRC development. In this paper, we focus on the IRC waveform design based on the multi-symbol orthogonal frequency division multiplexing (OFDM) technique. In view of the defects resulting from high peak-to-mean envelope power ratios (PMEPRs) and high range sidelobes in IRC systems, an intelligent and effective IRC waveform design method jointly optimized with the PMEPR and peak-to-sidelobe ratio (PSLR) is proposed. Firstly, a flexible tone reservation (TR)-based IRC waveform structure is applied in both temporal and frequency domains, i.e., multi-symbol OFDM waveform. Secondly, the optimization problem considering PMEPR and PSLR and extending them to the Lp-norm form is reformulated. Then, the conjugate gradient of the objective function is analytically derived and the conjugate gradient algorithm (CGA) is presented to simultaneously improve the PMEPR and PSLR. Finally, the simulation results show that the proposed algorithm can efficiently generate IRC waveforms with an excellent PMEPR, PSLR, radar signal-to-noise ratio (SNR), and bit error rate (BER) performance.

4D Automotive Radar Sensing for Autonomous Vehicles: A Sparsity-Oriented Approach

We propose a high-resolution imaging radar system to enable high-fidelity four-dimensional (4D) sensing for autonomous driving, i.e., range, Doppler, azimuth, and elevation, through a joint sparsity design in frequency spectrum and array configurations. To accommodate a high number of automotive radars operating at the same frequency band while avoiding mutual interference, random sparse step-frequency waveform (RSSFW) is proposed to synthesize a large effective bandwidth to achieve high range resolution profiles. To mitigate high range sidelobes in RSSFW radars, optimal weights are designed to minimize the peak sidelobe level such that targets with a relatively small radar cross section are detectable without introducing high probability of false alarm. We extend the RSSFW concept to multi-input multi-output (MIMO) radar by applying phase codes along slow time to synthesize a two-dimensional (2D) sparse array with hundreds of virtual array elements to enable high-resolution direction finding in both azimuth and elevation. The 2D sparse array acts as a sub-Nyquist sampler of the corresponding uniform rectangular array (URA) with half-wavelength interelement spacing, and the corresponding URA response is recovered by completing a low-rank block Hankel matrix. Consequently, the high sidelobes in the azimuth and elevation spectra are greatly suppressed so that weak targets can be reliably detected. The proposed imaging radar provides point clouds with a resolution comparable to LiDAR but with a much lower cost. Numerical simulations are conducted to demonstrate the performance of the proposed 4D imaging radar system with joint sparsity in frequency spectrum and antenna arrays.

Noise radar range doppler imaging via 2D generalized smoothed‐ l 0

This paper presents an algorithm to enhance the range-Doppler imaging performance for noise radar. Traditional matched filtering based method suffers from high range and Doppler sidelobes, which makes the weak targets overwhelmed by the sidelobes of strong targets or clutters in the range-Doppler map. Sparse recovery based methods have been widely used to suppress such sidelobes, but most of them assume a repetitive transmit waveform, which cannot be applied to noise radar applications. In this letter, the range-Doppler imaging problem for noise radar is formulated as a sparse recovery model and solved by a 2D generalized smoothed-l0 algorithm. The proposed method can deal with the random waveforms varying among different pulses in noise radar. The robustness of the proposed method in strong noise and clutters is validated by simulation results.

Co-Located MIMO Radar Target Detection in Cluttered and Noisy Environment Based on 2D Block Sparse Recovery

In the co-located multiple input multiple output (MIMO) radar, the matched filter receiver suffers from high range sidelobes, since the waveforms originating from different transmitters cannot be fully orthogonal. Traditional sparse recovery based receivers can suppress the sidelobes by assuming the sparsity of range profiles. However, in most practical situations, the range profile is not sparse due to the presence of clutter. In this paper, an effective co-located MIMO radar target detection algorithm is proposed based on modified smoothed-l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> norm sparse recovery, by exploiting the 2D block sparsity of the range-Doppler profiles of targets corresponding to different transmit-receive pairs. The proposed method can enhance the target detection performance in co-located MIMO radar system, especially for those weak targets which may be overwhelmed by high-level sidelobes of strong targets and clutters, without sacrificing computational efficiency. With a well-designed regularization approach and an adaptive regularization parameter update technique, the proposed method is also robust in noisy environment. Simulation and experimental results validate the effectiveness of the proposed method.

Target detection method in passive bistatic radar

Owing to the advantages in detecting the low altitude and stealth target, passive bistatic radar (PBR) has received much attention in surveillance purposes. Due to the uncontrollable characteristic of the transmitted signal, a high level range or Doppler sidelobes may exist in the ambiguity function which will degrade the target detection performance. Mismatched filtering is a common method to deal with the ambiguity sidelobe problem. However, when mismatched filtering is applied, sidelobes cannot be eliminated completely. The residual sidelobes will cause false-alarm when the constant false alarm ratio (CFAR) is applied. To deal with this problem, a new target detection method based on preprocessing is proposed. In this new method, the ambiguity range and Doppler sidelobes are recognized and eliminated by the preprocessing method according to the prior information. CFAR is also employed to obtain the information of the target echo. Simulation results and results on real data illustrate the effectiveness of the proposed method.

Range sidelobe suppression for OFDM‐integrated radar and communication signal

To improve the RadCom system of performing both data transmission and radar-sensing functions, here a waveform design method for orthogonal frequency division multiplexing (OFDM) signal is proposed to solve the problem of high range sidelobe level in radar detection process while maintaining a reasonable channel capacity. The method only transmits data in the sub-channels with preferable channel quality. Then, calculate the weight of the chosen subcarriers through the convex optimisation method to traditionally minimise the peak-to-sidelobe (PSL) ratio. Simulation results prove that, compared with traditional range sidelobe suppression method, this algorithm is more suitable for RadCom system.

Waveform Design for Dual-Function Radar-Communication System With Golay Block Coding

In view of the defects that high range side lobes and high peak-to-average power radio (PAPR) in radar and communication integrated systems based on traditional orthogonal frequency division multiplexing (OFDM), a co-designed OFDM waveform based on Golay block coding for joint radar-communication system is proposed in this paper. The communication information is coded into Golay complementary sequences by Reed-Muller codes, which can not only reduce the PAPR of the system, but also can improve the error correction capability. However, the code rate of the algorithm will decrease rapidly with the increase of the number of subcarriers. Furthermore, the traditional block coding would impact on the final superimposed waveform performance due to phase randomness. Hence, a self-disarrange block coding algorithm is proposed. The radar and communication performance of the designed waveform, including wideband ambiguity function, range profile, PAPR, and bit error rate, is analyzed and simulated. The results demonstrate that the PAPR of the waveform and BER can be reduced effectively, while the range side lobes can be decreased for better radar detection performance.

Mismatched filter for transmit waveform with frequency notches

In order to reduce radar interference on communication systems within shared bands, the radar transmit waveform forms frequency notches in the shared bands. However, because of the notches, the auto-correlation of the transmit waveform with frequency notches leads to high-range sidelobes. In order to achieve low-range sidelobes, the authors propose a mismatched filter. The mismatched filter for the transmit waveform with frequency notches has the same range sidelobes as the auto-correlation of the transmit waveform without frequency notches at the expense of a signal-to-noise ratio (SNR) loss. Simulation and analysis results demonstrate that the proposed mismatched filter always has low sidelobes at the cost of a SNR loss. In addition, simulation results show that the SNR loss is acceptable even for the deep notches (i.e. 20 dB), when the ratio of the waveform energy in the shared bands to the total waveform energy is moderate (i.e. <8%). However, the SNR loss increases rapidly with the depth of notches, when the ratio is large.

Chaotic Phase-Coded Waveforms With Space-Time Complementary Coding for MIMO Radar Applications

A framework for designing orthogonal chaotic phase-coded waveforms with space-time complementary coding is proposed for multiple-input multiple-output (MIMO) radar applications. The phase-coded waveform set to be transmitted is generated with an arbitrary family size and an arbitrary code length by using chaotic sequences. Due to the properties of chaos, this chaotic waveform set has many advantages in performance, such as anti-interference and low probability of intercept. However, it cannot be directly exploited due to the high range sidelobes, mutual interferences, and Doppler intolerance. In order to widely implement it in practice, we optimize the chaotic phase-coded waveform set from two aspects. First, the autocorrelation property of the waveform is improved by transmitting complementary chaotic phase-coded waveforms, and an adaptive clonal selection algorithm is utilized to optimize a pair of complementary chaotic phase-coded pulses. Second, the crosscorrelation among different waveforms is eliminated by implementing space-time coding into the complementary pulses. Moreover, to enhance the detection ability for moving targets in MIMO radars, a method of weighting different pulses by a null space vector is utilized at the receiver to compensate the interpulse Doppler phase shift and accumulate different pulses coherently. Simulation results demonstrate the efficiency of our proposed method.

Waveform design with low range sidelobe and high Doppler tolerance for cognitive radar

This paper considers the unimodular Linear-FM Synthesized (LFM-Syn) waveform design for cognitive radar.Firstly, the synthesized waveform is formulated by a given phase-scaling factor which combines the random noise waveform and the conventional LFM waveform. Secondly, to achieve low range sidelobes and high Doppler tolerance of LFM-Syn waveforms, a novel template-optimizing objective function is established and then transformed into a two-variable non-convex optimization case with constraints on quadratic phase and random phase. Meanwhile, a Relaxed Alternating Projection Phase Control method (RAPPC) incorporating spectrum approximation relaxed alternating projection and quadratic phase amendment is proposed via an iterative way. RAPPC not only enhances local exploiting for desired waveforms but also keeps high Doppler tolerance and low range sidelobes. Lastly, simulations have provided evidences that the LFM-Syn waveform optimized by RAPPC 1) has high Doppler tolerance similar to conventional LFM, 2) has Low Probability of Intercept (LPI) similar to random noise waveform, and 3) has low range sidelobe levels for prescribed requirement. Additionally, simulations also highlight the superior performance of our proposed algorithms over several existing techniques.

The Generalized Sinusoidal Frequency-Modulated Waveform for Active Sonar

Pulse compression (PC) active sonar waveforms provide a significant improvement in range resolution over single-frequency sinusoidal waveforms also known as continuous wave (CW) waveforms. Since their inception in the 1940s, a wide variety of PC waveforms have been designed using either frequency modulation (FM), phase coding, or frequency hopping to suite particular sonar applications. The sinusoidal FM (SFM) waveform modulates its instantaneous frequency (IF) by a sinusoid to achieve high Doppler sensitivity which also aids in suppressing reverberation. This allows the SFM waveform to resolve target velocities. While the SFM's resolution in range is inversely proportional to its bandwidth, the SFM's autocorrelation function (ACF) contains many large sidelobes. The periodicity of the SFM's IF creates these sidelobes and impairs the SFM's ability to clearly distinguish multiple targets in range. This paper describes a generalization of the SFM waveform, referred to as the generalized SFM (GSFM) waveform, which modifies the SFM's IF to resemble the time/voltage characteristic of an FM chirp waveform. As a result of this modification, the Doppler sensitivity of the SFM is preserved while substantially reducing the high range sidelobes, producing a waveform whose ambiguity function (AF) approaches a thumbtack shape. This paper focuses primarily on the properties of the GSFM's thumbtack AF shape and compares it to other well-known waveforms with a similar AF shape. The GSFM waveform achieves zero range-Doppler coupling for single target measurements which in turn minimizes the variance in jointly estimating target range and velocity and optimizes resolution of multiple point targets in range and velocity. The GSFM's AF peak sidelobe levels, which determine the waveform's ability to detect weak targets in the presence of strong ones, are comparable to other well-established thumbtack AF waveforms such as Costas or phase-coded waveforms over a wide range of time-bandwidth product (TBP) values.

Low-rate sampling technique for range-windowed radar/sonar using nonlinear frequency modulation

This paper proposes a new radar/sonar processing architecture that enables a low-rate time-sampling rate while still producing a high-resolution range profile over a narrow range-window. This new architecture generalizes the conventional “stretch processing” architecture (which employs linear frequency modulated (LFM) waveforms that suffer from high range-sidelobes), to nonlinear frequency modulated (NLFM) waveforms, which can lower the range-sidelobes without tapering. Computational results demonstrate both the estimation efficacy and the time-sampling efficiency of the proposed scheme.

A New Algorithm for Sparse Frequency Waveform Design with Range Sidelobes Constraint

To suppress narrowband interferences, sparse frequency waveform can be transmitted by wideband radar systems. It suffers the high range sidelobes. A new algorithm for sparse frequency waveform design with range sidelobes constraint is proposed. The approach affords much better frequency stopband suppression by flexibly controlling sidelobes constraint using Weighted integrated sidelobe level (WISL) metric. The approach is computationally efficient and can suit the more general Peakto- average power ratio (PAR) constraint. An extension to Multiple-input multiple-output (MIMO) radar case is also presented.

Complementary‐based chaotic phase‐coded waveforms design for MIMO radar

This study deals with orthogonal waveform design for multi-input multi-output (MIMO) radar. Chaos is introduced to generate orthogonal phase-coded waveforms of arbitrary coded length for arbitrary number of transmitters. However, most of these chaos-based waveforms suffer high range sidelobe level and intrapulse Doppler intolerance for pulse compression. A complementary transmitting structure is proposed for the MIMO radar to supress these high range sidelobes, and an adaptive clonal selection algorithm is introduced to search for the optimal complementary codes of the transmitted chaotic phase-coded waveform. This algorithm proves that it is convergent in theory as well. A multiple hypotheses approach is introduced at the transmitters to estimate and then compensate for the intrapulse Doppler phase shift for MIMO radar pulse compression countering the intrapulse Doppler intolerance. Numerical simulations with four typical chaotic maps are carried out and compared with Deng's codes, which validate the proposed methods of this study.

Chirp-encoded excitation for dual-frequency ultrasound tissue harmonic imaging

Dual-frequency (DF) transmit waveforms comprise signals at two different frequencies. With a DF transmit waveform operating at both fundamental frequency (f(0)) and second-harmonic frequency (2f(0)), tissue harmonic imaging can be simultaneously performed using not only the conventional 2f(0) second-harmonic signal but also using the f(0 )frequency-difference harmonic signal. Nonetheless, when chirp excitation is incorporated into the DF transmit waveform for harmonic SNR improvement, a particular waveform design is required to maintain the bandwidth of the f(0) harmonic signal. In this study, two different DF chirp waveforms are proposed to produce equal harmonic bandwidth at both the f(0) and 2f(0) frequencies to achieve speckle reduction by harmonic spectral compounding and to increase harmonic SNR for enhanced penetration and sensitivity. The UU13 waveform comprises an up-sweeping f(0) chirp and an up-sweeping 2f(0) chirp with triple bandwidth, whereas the UD11 waveform includes an up-sweeping f(0) chirp and a down-sweeping 2f(0) chirp with equal bandwidth. Experimental results indicate that the UU13 tends to suffer from a high range side lobe level resulting from 3f(0) interference. Consequently, the 2f(0) harmonic envelopes of the UD11 and the UU13 waveforms have compression qualities of 87% and 77%, respectively, when the signal bandwidth is 30%. When the bandwidth increases to 50%, the compression quality of the 2f(0) harmonic envelope degrades to 78% and 54%, respectively, for the UD11 and the UU13 waveforms. The compression quality value of the f0 harmonic envelope remains similar between the two DF transmit waveforms for all signal bandwidths. B-mode harmonic images also show that the UD11 is less contaminated by range side lobe artifacts than is the UU13. Compared with a short pulse with equal bandwidth, the UD11 waveform not only preserves the same spatial resolution after compression but also improves the image SNR by about 10 dB. Moreover, the image contrast-to-noise ratio (CNR), defined as the ratio of the mean to the standard deviation of image intensity in the speckle region, can be increased from 1.0 to about 1.2 when DF spectral compounding is performed. Therefore, it is concluded that the UD11 waveform is a potential solution for chirp-encoded DF harmonic imaging.

Multi-Target Performance of LMMSE Filtering in Radar

Coded orthogonal frequency division multiplexing (OFDM), like several other coded waveforms, exhibits inherent high range sidelobes after matched filtering. Consequently special processing at the receiver is required that can serve for sidelobe suppression in order to avoid target masking. However unmasking is not the only concern. It is crucial to evaluate the filtering scheme both in terms of sidelobe suppression capability and in terms of output signal-to-noise ratio (SNR). This last criterion is essential when aiming at detecting weaker reflections also. The theoretical performance of the reiterated filtering technique based on the linear minimum mean square error (LMMSE), as implemented in the adaptive pulse compression (APC) scheme, is derived and compared with the matched filter (MF). The analysis of the performance is done for a multi-target scenario where targets are close enough for the sidelobes of a target to interfere with the mainlobe of another target. Consequently the unmasking capabilities are relevant, but also output power figures. Complex-valued filter output peaks are also evaluated and compared with the MF output peaks. Moreover the performance of the method is evaluated for OFDM communication-encoded radar waveforms and compared with linear frequency modulated waveforms aiming at simultaneous use of the radar signal for both communication and radar.

High Resolution Range Imaging and Sidelobe Suppression Based on FD-MIMO Radar

High Resolution Range Imaging and Sidelobe Suppression Based on FD-MIMO Radar