Integrated Sensing and Communication （ISAC） has become a pivotal technology for 6G networks， addressing the increasing demands for data transmission and environmental awareness in advanced applications such as autonomous vehicles and smart IoT homes. However， conventional Radio Frequency （RF）-based ISAC systems face inherent challenges， including limited bandwidth， susceptibility to electromagnetic interference， and frequency-dependent losses， which constrain their ability to generate and process high-frequency broadband signals. Microwave Photonics （MWP） has emerged as a transformative solution that leverages optical technologies to overcome electronic bottlenecks， offering three key advantages： high-bandwidth signal processing capability， inherent immunity to RF interference， and a compact architecture with low power consumption. In communication systems， traditional multiplexing methods—such as Time Division Multiplexing （TDM）， Frequency Division Multiplexing （FDM）， and hybrid approaches—have been widely employed to enhance channel efficiency. Nevertheless， these methods exhibit limited resilience to interference. Code Division Multiplexing （CDM）， a well-established wireless technology derived from spread spectrum communication， uses unique codes to differentiate user data， enabling simultaneous transmission over the same frequency band for multiple users. CDM provides three significant benefits： robust multiple-access capability， intrinsic resistance to multipath interference， and improved signal security. Although prior research has demonstrated the potential of CDM， the integration of photonic-based Code Division Multiple Access （CDMA） with ISAC systems remains an underexplored area that warrants further investigation.

To address this research gap， we introduce a photonics-based ISAC system that combines spread spectrum coding， CDMA， and chirp waveform modulation. The proposed scheme features two main innovations： First， it achieves orthogonalization of user signals through specialized spread spectrum codes and scrambling sequences， effectively reducing random noise， inter-user interference， and multipath effects. This significantly enhances interference resistance and enables multi-user scalability. Second， the DC-biased spread spectrum encoding applied to Linear Frequency Modulation （LFM） signals generates integrated waveforms with unique chirp-phase characteristics and improved cross-correlation performance. This approach not only supports synchronization of communication sequences but also facilitates radar sensing via simplified photonic de-chirping processing， substantially lowering the Analog-to-Digital Converter （ADC） sampling rate requirements in radar receivers. For 3D positioning， we employ the Time Difference of Arrival （TDOA） method combined with a Chan-Taylor hybrid algorithm， enabling accurate localization with smaller network overhead. This integration of communication， sensing， and measurement systems has been successfully realized. Simulation results demonstrate the system's robustness： even under negative Signal-to-Interference-plus-Noise Ratio （SINR） conditions， spread spectrum phase coding sustains simultaneous multi-user communication and sensing. The system achieves decimeter-level distance resolution and high-precision near-field positioning. Parameter analysis evaluates the impact of DC bias， Voltage Peak-to-Peak （Vpp）， Received Optical Power （ROP）， and gain on communication performance in terms of Bit Error Rate （BER） and Signal-to-Interference Ratio （SIR）.

This research provides valuable insights for designing high-performance， interference-resistant integrated sensing and communication systems applicable to areas such as UAV control and management， smart homes， and intelligent transportation.