Search

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 of a distributed MIMO radar system via maximizing its peak. HighlightsTransmit signals are designed to maximize the ambiguity function's peak of a WS-MIMO radar.Signal design is done for three cases of single target, multi-target, and prioritized ambiguity function.It is shown that in spite of increasing the number of antennas of MIMO radar, signal design does not provide diversity gain.Through simulations, it is shown that better performance can be achieved by the proposed signal design to maximize the AF's peak.

It is presumed that using multiple antennas at the transmit and receive sides can improve the radar's performance. One such improvement can be achieved in the detection of extended targets. However, in such multiple-input multiple-output systems, proper design of the transmit signals is an obstacle that can have significant influence on the performance. In this study, enforcing the peak-to-average-ratio (PAR) constraint, the authors consider the problem of transmit space-time code and receive space-time filter design of such a system detecting extended targets. In addition, the power allocation among the different antennas is another degree of freedom that should be optimised under a total power constraint. Here, the authors derive a constrained optimisation procedure for transmit code, receive filter and transmit powers, which sequentially improves the signal-to-interference plus noise ratio of the system.

The authors deal with the robust design of multiple-input–multiple-output (MIMO) space–time transmit code (STTC) and space–time receive filter (STRF) for a point-like target embedded in signal-dependent interference. Specifically, they assume that the radar exploits knowledge provided by dynamic environmental database, to roughly predict the actual scattering scenario. Then, they devise an iterative method to optimise the (constrained) STTC and the (constrained) STRF which sequentially improves the worst-case (over interfering scatterers statistics) signal-to-interference-plus-noise ratio (SINR). Each iteration of the algorithm is handled via solving two (hidden) convex optimisation problems. The resulting computational complexity is linear with the number of iterations and polynomial with the sizes of the STTC and the STRF. At the analysis stage, they assess the performance of the proposed algorithm in terms of the achieved SINR. They show that properly exploiting the spatial degrees of freedom offered by the MIMO system, it is possible to obtain considerable SINR gains with respect to the conventional single-input–single-output system. Moreover, their results highlight the capability of the proposed method to robustify the performance of the designed system against possible knowledge inaccuracies.

Efficient combination of MIMO (multiple-input multiple-output) and PCL (passive coherent location) ideas is expected to improve performance of localization schemes. While, in general, adding the number of transmit and receive antennas provides spatial diversity, it is possible to obtain similar effects by using multiple transmitters that are already transmitting standard signals (such as digital TV (DTV) transmission) in the environment (also known as illuminators of opportunity). However, in the case of passive schemes, it is not always possible to ensure that signals of different transmitters are orthogonal to each other. In such cases in which nonorthogonal transmitter signals are to be used, resolving signals of multiple transmitters reflected from multiple objects is not a trivial problem. One such scenario arises when transmitters of a single frequency network (SFN) are used. Consequently, in order to obtain the desired diversity gain and maintain the correct localization, it is necessary to develop proper techniques to assign each echo that arrives at the receivers to a given transmitter and a specific object that is to be localized. We propose a scheme that addresses the association problem in an efficient way.

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.

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.

In this paper, we devise a joint code-filter design method to optimize the signal-to-interference-plus-noise ratio (SINR) associated with the colocated MIMO radars. We consider constant-modulus wavefrom design for moving target detection and propose a cyclic algorithm to deal with the design problem.

We propose a novel robust design method to jointly optimize the radar transmit code and receive filter, exploiting the signal-to-interference-plus-noise ratio (SINR) at the receiver end as design figure of merit. We confer robustness to our method against uncertainties on the target impulse response (TIR) using a worst-case optimization approach. Precisely, we model the uncertainty set as a finite collection of TIRs, obtained sampling the actual TIR at some aspect angles. We further enforce a peak-to-average power ratio (PAR) constraint to the transmit code, which is very important for radar applications, where the transmitter operates close to saturation. The design problem is tackled using a sequential optimization procedure alternating between two semi-definite programming (SDP) problems, followed by randomization steps. Our numerical results highlight the robustness and applicability of the proposed method.

Efficient combination of multiple input multiple output (MIMO) and passive coherent location (PCL) ideas is expected to improve performance of localisation schemes. While using multiple antennas at transmit and receive sides provides spatial diversity, it is possible to obtain similar performance by using multiple transmitters, already transmitting standard signals (such as digital TV) in the environment (also known as illuminators of opportunity). However, in this case, it is not always possible to ensure that signals of different transmitters are orthogonal to each other. In such cases, resolving signals of multiple transmitters reflected from multiple objects is not a trivial problem. One such scenario arises when transmitters of a single frequency network (SFN) are used. Consequently, in order to obtain the desired diversity gain, it is necessary to develop proper techniques to assign each echo arriving at the receiver to a given transmitter and a specific object to be localised. In this paper, we propose a scheme that addresses the association problem in an efficient way. Also, we consider the case of multiple antennas only at the transmit side while using a single receiver, which is the case of a multi-input single-output (MISO) system, a subset of MIMO systems, in general.