Many sensing tasks, such as plant stress sensing and blood pressure estimation, require co-located multi-modal measurements from two to five sensors at one site. RF backscatter enables low-power sensing, but existing tags usually support only one sensor; using multiple tags increases footprint and antenna coupling. We present Matrix, a fully-analog single-chain backscatter tag that supports multiple onboard sensors by multiplexing them into a composite voltage for transmission through one analog modulation chain. Unlike time-division polling, which introduces inter-sensor sampling offsets, or frequency-division, which requires separate chains, Matrix uses voltage-division multiplexing. Each sensor is encoded as a PWM waveform whose duty cycle represents the measurement, while amplitude enables multiplexing. Binary-weighted voltage-division weights make each active-sensor set uniquely invertible for reliable demultiplexing. The composite voltage is then converted into backscatter frequency shifts through the same chain. At the receiver, Matrix uses a Hidden Markov Model to recover per-sensor readings. Its ASIC consumes 25.56μW. A five-sensor prototype achieves 20 dB average reconstruction SNR at 30 kHz sampling, and we validate Matrix in plant sensing, health monitoring, and microphone-based direction finding.