Sharif Digital Repository

An important tool for assessing a radar's performance is the ambiguity function. On the other hand, many different schemes have been designed for the transmit waveforms of a MIMO radar. For each one, a criterion has been chosen to improve the performace, e.g. achieving better missed detection. In this paper, considering the ambiguity function as the benchmark, we propose a waveform design scheme, which optimizes the ambiguity function of the MIMO radar system  

Masking effect is the most important problem in Noise Radars. Recently, some waveform design methods to resolve this problem have been developed, however this paper will show an important fact: 'sidelobe suppression increases the Periodicity of signal and, consequently, decreases unpredictability'. Eventually, an appropriate level for sidelobe reduction is introduced  

In noise radars, measuring the cross-correlation between transmitted and received signals is known as a common method of signal processing. However, it brings a lot of unwelcome sidelobes which can lean to masking weak echoes of far targets. There are many classical and modern methods of masking effect removal which are based on signal processing in the receiver side. A method of waveform design for decreasing this effect is presented and its efficiency is compared to purely random waveform generation method and CLEAN algorithm. Moreover, performance of collaborative using of receiver-based and transmitter-based techniques is considered  

Signal processing in noise radar is always done by calculating the cross-correlation between transmitted and received signals. Strong echoes of near targets present relatively high sidelobes in the correlation output, so they can conceal weak echoes of weak targets (masking effect). Many classical and modern methods for alleviating this effect have been offered, however, most of them are based on signal processing in the receiver side. In this paper, a new method of waveform design, able to decrease masking effect, is presented. Contrary to the other methods, this method keeps the matched filter structure in receiver unchanged and does not need performing any extra process in the receiver... 

Compressive sensing (CS) is a widely used technique for (multiple) target detection in multiple input multiple output (MIMO) radars. In this paper, our goal is to enhance the quality of CS-based detection techniques for a colocated MIMO radar with given location of transmit and receive nodes. Our approach is to design the transmit waveforms based on the given antenna locations and optimally allocate the total power budget among the transmitters. The design criterion in this paper is the coherence of the resulting sensing matrix. Based on this criterion, we derive and solve a convex optimization problem for power allocation. For waveform design, however, the direct method studied is... 

In this letter, we consider the problem of waveform design in colocated multiple-input multiple-output radars in order to obtain a desired beampattern. In this problem, practical constraints, such as constant envelope (CE) and low peak-to-average power ratio, are very important. Therefore, we propose a simple method to generate some practical waveforms, such as different versions of phase-shift keying and pulse-amplitude modulation. We map a non-CE to the desired finite alphabet by a mapping function (MP). In the proposed method, first, the values of cross-correlation relationship between the input and the output of MP are calculated in a few points, and then, using radial point... 

In noise radars, measuring the cross-correlation between transmitted and received signals is a common method of signal processing. However, it brings a lot of unwelcome sidelobes that can mask weak echoes of far targets. There are many classical and modern methods of masking effect removal which are based on signal processing in the receiver side. In this study, a method of waveform design is presented and its ability to reduce masking effect is compared with that of radars using purely random waveforms. The method starts with choosing an arbitrary subsequence and continues with attaching new subsequences to the previous ones in a way that the sidelobe levels reduce. In addition, the... 

In this paper, the problem of designing waveform for MIMO-SAR systems is investigated. The family of modified Costas pulses (MCP) are used because of their advantages. However, a MIMO-SAR system will not be beneficial unless the waveforms transmitted through different antennas are orthogonal, even under different delay/Doppler shifts. An iterative algorithm is proposed that finds a set of MCPs and guarantees that the maximum cross-correlation (under different Doppler/delay shifts) among different waveforms is below a threshold. Simulation results show that the proposed waveform design outperforms the conventional one in terms of orthogonality, resolution, and signal-Tointerference-plus-noise... 

One of the important obstacles in MIMO (Multiple Input Multiple Output) radars is the issue of designing proper transmit signals. Indeed, the capability of signal design is a significant advantage in MIMO radars, through which, the system can achieve much better performance. Many different aspects of this performance improvement have been considered yet, and the transmit signals have been designed to attain such goal, e.g., getting higher SNR or better detector's performance at the receiver. However, an important tool for evaluating the radar's performance is its ambiguity function. In this paper, we consider the problem of transmit signal design, in order to optimize the ambiguity function... 

This paper will design non-linear frequency modulation (NLFM) signal for Chebyshev, Kaiser, Taylor, and raised-cosine power spectral densities (PSDs). Then, the variation of peak sidelobe level with regard to mainlobe width for these four different window functions are analyzed. It has been demonstrated that reduction of sidelobe level in NLFM signal can lead to increase in mainlobe width of autocorrelation function. Furthermore, the results of power spectral density obtained from the simulation and the desired PSD are compared. Finally, error percentage between simulated PSD and desired PSD for different peak sidelobe level are illustrated. The stationary phase concept is the possible... 

Waveform design for Target identification and classification in MIMO radar systems has been studied in several recent works. While the previous works considered signal independent noise, here we extend the results to the case where signal-dependent noise, clutter, is also present and then we find the optimum waveform for several estimators differing in the assumptions on the given statistics. Computing the optimal waveforms for MMSE estimator leads to the Semi-definite programming (SDP) problem. Finding the optimal transmit signals for CSLS estimator results in a minimax eigenvalue problem. Finally it is shown that equal power waveforms are the best transmit signals for the SLS estimator.... 

In a MIMO (Multiple Input Multiple Output) radar system, proper design of transmit signal and receive filter is an advantageous tool to improve the detection performance. Thus, in this paper, we consider the problem of transmit code and receive filter design, in order to maximize the Signal to Noise Ratio (SNR) at the receiver while enforcing a similarity constraint between the transmit space-time code (STC) and a reference STC which has a desirable ambiguity function. We will show that by solving such constrained optimization problem through successive iterations, our proposed method leads to satisfactory results  

A new optimal waveform for Ultra-wideband (UWB) radios is proposed in this paper. This new waveform extracted through mathematical analysis for achieving high spectral utilization under the restrictions imposed by the U.S. Federal Communications Commission (FCC) spectral masks. Exploiting Inverse Fourier Transform (IFT) of FCC mask, the required analog signals are extracted through robust calculation and the optimum realizable analog signal for FCC mask is constructed while the simulations confirmed the analytical approach. Normalized effective signal power (NESP) of the proposed method is 95.27% which shows better efficiency compared to the other methods in the literature  

Waveform design for target identification and classification in MIMO radar systems has been studied in several recent works. While the previous works assumed that the noise was independent of the transmission signals, here we extend the results to the signal dependent noise (clutter). We consider two scenarios. In the first scenario it is assumed that different transmit antennas see uncorrelated aspects of the target. In the second scenario, we consider the correlated target. As clutter is dependent to signal, target estimation error cannot vanish only by increasing the transmission power. It can be shown that in the second scenario, MIMO radar receiver can nullify the clutter subspace.... 

Waveform design for Target identification and classification in MIMO radar systems has been studied in several recent works. While the previous works considered signal independent noise and found optimal signals for an e stimation algorithm, here we extend the results to the case where clutter is also present and then we will find the optimum waveform for several estimators differing in the assumptions on the given statistics. Several different approaches to the optimal waveform design are proposed, including minimizing the error of MMSE estimator, minimizing the maximum error of the covariance shaping least square (CSLS) estimator and minimizing the MSE error of scaled least square (SLS)...