Unmanned aerial vehicle (UAV) swarms require accurate relative localization to safeguard flight missions in the global navigation satellite system-denied environment due to a lack of absolute position information. The existing work of relative localization faces challenges, such as the ranging information loss and the low localization frequency caused by long-distance ranging and large-scale characteristic of the UAV swarm. This article proposes a clustering-based cooperative relative localization scheme for UAV swarm, which contains a two-level framework: inter/intra-cluster localization. In order to investigate the tradeoff between intracluster cooperation and intercluster packet loss, the clustering-based problem is constructed as a coalition formation game (CFG) model. Given the designed coalition value, preference relation, and the coalition formation principles, it is proved that the proposed CFG model has a Nash stable partition. The designed coalition formation algorithm includes coalition heads and beacon drones selection mechanism. Simulation results show that the proposed CFG algorithms shorten the ranging time compared with global localization and achieve better localization performance (localization error and success rate) than contrast algorithms.

This paper presents a mixed-decimation multipath delay feedback (M2 DF) approach for the radix-2 ^k fast Fourier transform. We employ the principle of folding transformation to derive the proposed architecture, which activates the idle period of arithmetic modules in multipath delay feedback (MDF) architectures by integrating the decimation-in-time operations into the decimation-in-frequency-operated computing units. Furthermore, we compare the proposed design with other efficient schemes, namely, the MDF and the multipath delay commutator (MDC) scheme theoretically and experimentally. Relying on the obtained expressions and statistics, it can be concluded that the M2DF design serves as an efficient alternative to the MDF scheme, since it achieves improved efficiency in the utilization of arithmetic resources without deteriorating the superiorities of feedback structures. In addition, the recommended design performs better in memory requirement and computing delay compared with the MDC approach.

The scheduling of data access plays a prominent part in a memory-based fast Fourier transform (FFT) processor. In this article, a conflict-free data-access scheme is proposed and applied to implement a radix-2^k FFT processor with the computing parallelism being the power of 2. The proposed FFT module exploits single-port RAMs to retain the area efficiency, and it has the following hardware-friendly features. First, the memories are merged into four banks under the arbitrary computing parallelism, which helps to circumvent the complicated data-routing circuit. Second, the parallelism of the input/output (I/O) data can be enlarged to the internal computing parallelism, which accelerates the data update and enhances the throughput capability. Furthermore, the concurrent I/O operation that overlaps the storage of the FFT input with the supply of FFT output in the same memory sets is allowed, which minimizes the memory occupation for the management of continuous data flow. Based on the testing on the field-programmable gate array (FPGA) and ASIC implementation using the SMIC 40-nm CMOS technology, it is demonstrated that the proposed FFT processor can offer high throughput and simultaneously achieve remarkable area and power efficiency.

With the development of acoustic localization schemes using mobile devices, keystroke detection has received tremendous attention from the academia and industry. Currently, most of the existing systems focus on the recognition of a single keystroke and they are limited by several restrictions. In this paper, we consider the idea of signal variation caused by the combination of two combined keystrokes, and propose an acoustic-based scheme that can detect the combined keystrokes effectively. Our system exploits the blind signal separation technique to deal with the mixed signals, resultant from typing two separate keys simultaneously. Then, we apply feature extraction and pattern recognition algorithms to recognize the combined keystrokes. Extensive experiments have been conducted in a laboratory environment with mobile phones equipped with two microphones. Our results show that for several combinations of two keystrokes, on average, we can achieve 78.4% recognition accuracy.

The radix- 2 ^k algorithm plays a crucial role in the pipelined implementation of fast Fourier transform (FFT). This paper presents a fixed-point analysis and hardware evaluation of radix- 2 ^k FFT under the framework of the single-path delay feedback (SDF) and multi-path delay commutator (MDC) pipelined structure. The investigation is carried out with variable operating word-lengths to ensure the generality. Furthermore, the main streams to fulfill FFT coefficients weighting, namely, the approach using complex multipliers and the one adopting memoryless CORDIC units, are both considered in the analysis. Based on these derivations, a joint optimization of radix- 2 ^k algorithm and operating word-length is discussed to achieve a reasonable trade-off between computational accuracy and hardware expenditure. Simulations and experiments indicates that the derived SQNR is reliable to unfold the quantization effects of fixed-point radix- 2 ^k FFT. In addition, the proposed joint optimization strategy is capable of providing better solutions to implement the radix- 2 ^k FFT processor efficiently.

The two-dimensional spectrum sensing that jointly acquires angular locations and frequency responses of multiple emitters is an important issue for cognitive radio. This paper presents a two-step algorithm to address this issue for the uniform linear array. In the coarse sensing step, we first apply fast Fourier transform to the mixed signal of each antenna. Then the mixed responses occupying the same frequency grid are collected from different antennas for roughly estimating spatial angles and the corresponding frequency magnitudes, where we resort to the harmonic analysis and explores spatial angles over the continuum. In the refined estimation step, the obtained angle-frequency data pairs are screened to eliminate false-alarm ones, based on which the spatial angles and the relevant spectrums are jointly regulated. Compared with the current works, the number of emitters is not a mandatory information for the proposed design, and it can be also well-suited to the correlated sources and the data-starving scenario. Numerical simulations demonstrate the merits of proposed algorithm, which can considerably improve the sensing accuracy with low computational burden.