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This paper studies the Two-Person Zero Sum(TPZS) game between a Multiple-Input Multiple-Output(MIMO) radar and an extended target with payoff function being the output Signal-to-Interference-pulse-Noise Ratio(SINR) at the radar receiver. The radar player wants to maximize SINR by adjusting its transmit waveform and receive filter. Conversely, the target player wants to minimize SINR by changing its Target Impulse Response(TIR) from a scaled sphere centered around a certain TIR. The interaction between them forms a Stackelberg game where the radar player acts as a leader. The Stackelberg equilibrium strategy of radar, namely robust or minimax waveform-filter pair, for three different cases are taken into consideration. In the first case, Energy Constraint(EC) on transmit waveform is introduced, where we theoretically prove that the Stackelberg equilibrium is also the Nash equilibrium of the game, and propose Algorithm 1 to solve the optimal waveform-filter pair through convex optimization. Note that the EC cant meet the demands of radar transmitter due to high Peak Average to power Ratio(PAR) of the transmit waveform, thus Constant Modulus and Similarity Constraint(CM-SC) on waveform is considered in the second case, and Algorithm 2 is proposed to solve this problem, where we theoretically prove the existence of Nash equilibrium for its Semi-Definite Programming(SDP) relaxation form. And the optimal waveform-filter pair is solved by calculating the Nash equilibrium followed by the randomization schemes. In the third case,...
The existence of multipath brings extra looks of targets. This paper considers the extended target detection problem with a narrow band Multiple-Input Multiple-Output(MIMO) radar in the presence of multipath from the view of waveform-filter design. T
Frequency-hopping (FH) MIMO radar-based dual-function radar communication (FH-MIMO DFRC) enables communication symbol rate to exceed radar pulse repetition frequency, which requires accurate estimations of timing offset and channel parameters. The es
Dual-functional radar-communication (DFRC) systems can simultaneously perform both radar and communication functionalities using the same hardware platform and spectrum resource. In this paper, we consider multi-input multi-output (MIMO) DFRC systems
MIMO transmit arrays allow for flexible design of the transmit beampattern. However, the large number of elements required to achieve certain performance using uniform linear arrays (ULA) maybe be too costly. This motivated the need for thinned array
The problem of data-driven joint design of transmitted waveform and detector in a radar system is addressed in this paper. We propose two novel learning-based approaches to waveform and detector design based on end-to-end training of the radar system