The configurable Ring oscillator Physical unclonable function (CRO PUF) is the newly proposed strong PUF based on classic RO PUF, which can generate exponential Challenge-Response Pairs (CRPs) and has good uniqueness and reliability. However, existing proposals have low hardware utilization and vulnerability to modeling attacks. In this paper, we propose a Novel Configurable Dual State (CDS) PUF with lower overhead and higher resistance to modeling attacks. This structure can be flexibly transformed into RO PUF and TERO PUF in the same topology according to the parity of the Hamming Weight (HW) of the challenge, which can achieve 100% utilization of the inverters and improve the efficiency of hardware utilization. A feedback obfuscation mechanism (FOM) is also proposed, which uses the stable count value of the ring oscillator in the PUF as the updated mask to confuse and hide the original challenge, significantly improving the effect of resisting modeling attacks. The proposed FOM-CDS PUF is analyzed by building a mathematical model and finally implemented on Xilinx Artix-7 FPGA, the test results show that the FOM-CDS PUF can effectively resist several popular modeling attack methods and the prediction accuracy is below 60%. Meanwhile it shows that the FOM-CDS PUF has good performance with uniformity, Bit Error Rate at different temperatures, Bit Error Rate at different voltages and uniqueness of 53.68%, 7.91%, 5.64% and 50.33% respectively.

In this paper, we consider the problem of waveform optimization for multi-input multi-output (MIMO) radar in the presence of signal-dependent noise. A novel diagonal loading (DL) based method is proposed to optimize the waveform covariance matrix (WCM) for minimizing the Cramer-Rao bound (CRB) which improves the performance of parameter estimation. The resulting nonlinear optimization problem is solved by resorting to a convex relaxation that belongs to the semidefinite programming (SDP) class. An optimal solution to the initial problem is then constructed through a suitable approximation to an optimal solution of the relaxed one (in a least squares (LS) sense). Numerical results show that the performance of parameter estimation can be improved considerably by the proposed method compared to uncorrelated waveforms.

The composite binary offset carrier (CBOC) modulated signal contains multi-peaks in its auto-correlation function, which brings ambiguity to the signal acquisition process of a GNSS receiver. Currently, most traditional ambiguity-removing schemes for CBOC signal acquisition approximate CBOC signal as a BOC signal, which may incur performance degradation. Based on Galileo E1 CBOC signal, this paper proposes a novel adaptive ambiguity-removing acquisition scheme which doesn't adopt the approximation used in traditional schemes. According to the energy ratio of each sub-code of CBOC signal, the proposed scheme can self-adjust its local reference code to achieve unambiguous and precise signal synchronization. Monte Carlo simulation is conducted in this paper to analyze the performance of the proposed scheme and three traditional schemes. Simulation results show that the proposed scheme has higher detection probability and less mean acquisition time than the other three schemes, which verify the superiority of the proposed scheme.